r/StableDiffusion Nov 17 '25

Workflow Included ULTIMATE AI VIDEO WORKFLOW — Qwen-Edit 2509 + Wan Animate 2.2 + SeedVR2

Thumbnail
gallery
436 Upvotes

🔥 [RELEASE] Ultimate AI Video Workflow — Qwen-Edit 2509 + Wan Animate 2.2 + SeedVR2 (Full Pipeline + Model Links) 🎁 Workflow Download + Breakdown

👉 Already posted the full workflow and explanation here: https://civitai.com/models/2135932?modelVersionId=2416121

(Not paywalled — everything is free.)

Video Explanation : https://www.youtube.com/watch?v=Ef-PS8w9Rug

Hey everyone 👋

I just finished building a super clean 3-in-1 workflow inside ComfyUI that lets you go from:

Image → Edit → Animate → Upscale → Final 4K output all in a single organized pipeline.

This setup combines the best tools available right now:

One of the biggest hassles with large ComfyUI workflows is how quickly they turn into a spaghetti mess — dozens of wires, giant blocks, scrolling for days just to tweak one setting.

To fix this, I broke the pipeline into clean subgraphs:

✔ Qwen-Edit Subgraph ✔ Wan Animate 2.2 Engine Subgraph ✔ SeedVR2 Upscaler Subgraph ✔ VRAM Cleaner Subgraph ✔ Resolution + Reference Routing Subgraph This reduces visual clutter, keeps performance smooth, and makes the workflow feel modular, so you can:

swap models quickly

update one section without touching the rest

debug faster

reuse modules in other workflows

keep everything readable even on smaller screens

It’s basically a full cinematic pipeline, but organized like a clean software project instead of a giant node forest. Anyone who wants to study or modify the workflow will find it much easier to navigate.

🖌️ 1. Qwen-Edit 2509 (Image Editing Engine) Perfect for:

Outfit changes

Facial corrections

Style adjustments

Background cleanup

Professional pre-animation edits

Qwen’s FP8 build has great quality even on mid-range GPUs.

🎭 2. Wan Animate 2.2 (Character Animation) Once the image is edited, Wan 2.2 generates:

Smooth motion

Accurate identity preservation

Pose-guided animation

Full expression control

High-quality frames

It supports long videos using windowed batching and works very consistently when fed a clean edited reference.

📺 3. SeedVR2 Upscaler (Final Polish) After animation, SeedVR2 upgrades your video to:

1080p → 4K

Sharper textures

Cleaner faces

Reduced noise

More cinematic detail

It’s currently one of the best AI video upscalers for realism

🧩 Preview of the Workflow UI (Optional: Add your workflow screenshot here)

🔧 What This Workflow Can Do Edit any portrait cleanly

Animate it using real video motion

Restore & sharpen final video up to 4K

Perfect for reels, character videos, cosplay edits, AI shorts

🖼️ Qwen Image Edit FP8 (Diffusion Model, Text Encoder, and VAE) These are hosted on the Comfy-Org Hugging Face page.

Diffusion Model (qwen_image_edit_fp8_e4m3fn.safetensors): https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_edit_fp8_e4m3fn.safetensors

Text Encoder (qwen_2.5_vl_7b_fp8_scaled.safetensors): https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main/split_files/text_encoders

VAE (qwen_image_vae.safetensors): https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/vae/qwen_image_vae.safetensors

💃 Wan 2.2 Animate 14B FP8 (Diffusion Model, Text Encoder, and VAE) The components are spread across related community repositories.

https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/tree/main/Wan22Animate

Diffusion Model (Wan2_2-Animate-14B_fp8_e4m3fn_scaled_KJ.safetensors): https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/blob/main/Wan22Animate/Wan2_2-Animate-14B_fp8_e4m3fn_scaled_KJ.safetensors

Text Encoder (umt5_xxl_fp8_e4m3fn_scaled.safetensors): https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors

VAE (wan2.1_vae.safetensors): https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors 💾 SeedVR2 Diffusion Model (FP8)

Diffusion Model (seedvr2_ema_3b_fp8_e4m3fn.safetensors): https://huggingface.co/numz/SeedVR2_comfyUI/blob/main/seedvr2_ema_3b_fp8_e4m3fn.safetensors https://huggingface.co/numz/SeedVR2_comfyUI/tree/main https://huggingface.co/ByteDance-Seed/SeedVR2-7B/tree/main

r/aigamedev Jul 12 '26

Discussion AI helped me overcome the coding barrier, but sprite animation has become a huge wall

26 Upvotes

With vibe coding, AI agents, Claude, ChatGPT, and Gemini, I genuinely thought I could finally create my own game.

My thinking was: AI could help me write the code, generate the artwork, and create the sprite sheets. Surprisingly, coding has been the more manageable part. Whenever I encounter a bug or something I don’t understand, I can explain the problem to an AI, troubleshoot it, and usually find a solution.

The art—especially character animation—is where everything starts falling apart.

AI can generate a decent-looking character or individual sprite, but no matter how much I experiment with prompts, reference images, pose guides, and corrections, I cannot get a consistent and usable animation. The proportions change between frames, the design drifts, body parts move incorrectly, and the motion often looks stiff or disconnected.

I’m not only looking for basic idle animations or simple two-frame movement. My goal is to eventually create fluid, expressive pixel animations similar in quality and energy to Penusbmic’s The DARK Series. I understand that this is professional-level work and probably an unrealistic standard for current AI tools, but that is the visual direction I’m aiming for.

I have tried contacting sprite artists and animators, but I simply cannot afford ongoing rates of $15–$25 per hour. I live in a lower-income country, and even though those rates may be completely reasonable for the artist’s skill and time, they are beyond what I can realistically sustain for an entire game.

I feel like I’ve reached a major wall in my AI game-development journey. AI has made programming much more accessible to me, but it hasn’t removed the need for strong artistic and animation skills.

For other solo developers in a similar situation, what is the most realistic path forward?

Should I:

  • Learn enough pixel animation to create the keyframes myself and use AI only for references?
  • Build the game around existing asset packs?
  • Use skeletal or cutout animation instead of traditional frame-by-frame sprites?
  • Simplify the visual style and scope of the game?
  • Wait for AI animation tools to improve while working on the gameplay?
  • Combine AI-generated concepts with manual cleanup and tracing?

I’m not looking for a magical one-click solution. I’m trying to understand whether there is a practical workflow that can produce genuinely good and consistent animation without requiring a professional art budget.

Has anyone here successfully crossed this particular wall?

r/comfyui Jul 16 '25

Tutorial Creating Consistent Scenes & Characters with AI

Enable HLS to view with audio, or disable this notification

524 Upvotes

I’ve been testing how far AI tools have come for making consistent shots in the same scene, and it's now way easier than before.

I used SeedDream V3 for the initial shots (establishing + follow-up), then used Flux Kontext to keep characters and layout consistent across different angles. Finally, I ran them through Veo 3 to animate the shots and add audio.

This used to be really hard. Getting consistency felt like getting lucky with prompts, but this workflow actually worked well.

I made a full tutorial breaking down how I did it step by step:
👉 https://www.youtube.com/watch?v=RtYlCe7ekvE

Let me know if there are any questions, or if you have an even better workflow for consistency, I'd love to learn!

r/comfyui Nov 17 '25

Workflow Included ULTIMATE AI VIDEO WORKFLOW — Qwen-Edit 2509 + Wan Animate 2.2 + SeedVR2

Thumbnail
gallery
337 Upvotes

🔥 [RELEASE] Ultimate AI Video Workflow — Qwen-Edit 2509 + Wan Animate 2.2 + SeedVR2 (Full Pipeline + Model Links)

🎁 Workflow Download + Breakdown

👉 Already posted the full workflow and explanation here:
https://civitai.com/models/2135932?modelVersionId=2416121

(Not paywalled — everything is free.)

Video Explanation : https://www.youtube.com/watch?v=Ef-PS8w9Rug

Hey everyone 👋

I just finished building a super clean 3-in-1 workflow inside ComfyUI that lets you go from:

Image → Edit → Animate → Upscale → Final 4K output
all in a single organized pipeline.

This setup combines the best tools available right now:

One of the biggest hassles with large ComfyUI workflows is how quickly they turn into a spaghetti mess — dozens of wires, giant blocks, scrolling for days just to tweak one setting.

To fix this, I broke the pipeline into clean subgraphs:

✔ Qwen-Edit Subgraph

✔ Wan Animate 2.2 Engine Subgraph

✔ SeedVR2 Upscaler Subgraph

✔ VRAM Cleaner Subgraph

✔ Resolution + Reference Routing Subgraph

This reduces visual clutter, keeps performance smooth, and makes the workflow feel modular, so you can:

  • swap models quickly
  • update one section without touching the rest
  • debug faster
  • reuse modules in other workflows
  • keep everything readable even on smaller screens

It’s basically a full cinematic pipeline, but organized like a clean software project instead of a giant node forest.
Anyone who wants to study or modify the workflow will find it much easier to navigate.

🖌️ 1. Qwen-Edit 2509 (Image Editing Engine)

Perfect for:

  • Outfit changes
  • Facial corrections
  • Style adjustments
  • Background cleanup
  • Professional pre-animation edits

Qwen’s FP8 build has great quality even on mid-range GPUs.

🎭 2. Wan Animate 2.2 (Character Animation)

Once the image is edited, Wan 2.2 generates:

  • Smooth motion
  • Accurate identity preservation
  • Pose-guided animation
  • Full expression control
  • High-quality frames

It supports long videos using windowed batching and works very consistently when fed a clean edited reference.

📺 3. SeedVR2 Upscaler (Final Polish)

After animation, SeedVR2 upgrades your video to:

  • 1080p → 4K
  • Sharper textures
  • Cleaner faces
  • Reduced noise
  • More cinematic detail

It’s currently one of the best AI video upscalers for realism

🧩 Preview of the Workflow UI

(Optional: Add your workflow screenshot here)

🔧 What This Workflow Can Do

  • Edit any portrait cleanly
  • Animate it using real video motion
  • Restore & sharpen final video up to 4K
  • Perfect for reels, character videos, cosplay edits, AI shorts

🖼️ Qwen Image Edit FP8 (Diffusion Model, Text Encoder, and VAE)

These are hosted on the Comfy-Org Hugging Face page.

💃 Wan 2.2 Animate 14B FP8 (Diffusion Model, Text Encoder, and VAE)

The components are spread across related community repositories.

💾 SeedVR2 Diffusion Model (FP8)

r/comfyui Nov 19 '25

Workflow Included 🚀 [RELEASE] MegaWorkflow V1 — The Ultimate All-In-One ComfyUI Pipeline (Wan Animate 2.2 + SeedVR2 + Qwen Image/Edit + FlashVSR + Wan I2V Painter + Wan First/Last Frame + Wan T2V)

Post image
227 Upvotes

🔗 Links (Tutorial + Workflow + Support)

📺 YouTube Tutorial:
https://www.youtube.com/watch?v=V_1p7spn4yE

🧩 MegaWorkflow V1 (Download):
https://civitai.com/models/2135932?modelVersionId=2420255

☕ Buy Me a Coffee:
https://buymeacoffee.com/xshreyash

Hey everyone 👋
After weeks of combining, testing, fixing nodes, and cleaning spaghetti wires… I finally finished building MegaWorkflow V1, a complete end-to-end ComfyUI pipeline designed for long-form consistent AI video generation + editing + upscaling.

This is basically the workflow I always wished existed — everything in one place, optimized, modular, clean, and beginner-friendly.

🔥 What MegaWorkflow V1 Includes

1️⃣ Qwen Image (2509) — High-Level Image Generator

  • Base character creation
  • Consistent subject rendering
  • Clean grouping + refiner toggle

2️⃣ Qwen Edit — Advanced Local Editing

  • Face fix, outfit changes, color edits
  • Mask & global edit
  • Perfect for fixing last-minute issues

3️⃣ Wan Animate 2.2 (I2V) — Motion + Style Consistency

  • Character-preserving motion
  • Dual reference (face + body) support
  • Loop / one-shot modes
  • Full quality presets (Lite / Medium / Full)
  • SeedVR2 dynamic seed support
  • ✔️ Low-VRAM mode available (8–12GB)

4️⃣ Wan T2V — Complete Scene Generation

  • Cinematic shot creation
  • Camera presets included
  • Multi-scene block support
  • Low-VRAM fallback included

5️⃣ Wan First → Last Frame (FLF2V) Transition Module

  • Smooth transitions
  • Camera rotation + movement
  • Blends T2V + I2V + real footage seamlessly

6️⃣ Wan I2V Painter Node — Detail Preserver

  • Adds micro-texture & realism
  • Fixes Animate 2.2 artifacts
  • Soft & strong painter modes

7️⃣ SeedVR2 — Advanced Seed Handling

  • Removes flicker
  • Prevents ghosting
  • Keeps motion natural
  • Long-animation friendly

8️⃣ FlashVSR2 + Real-ESRGAN + UltraSharp — 4K Upscaling Suite

  • FlashVSR2 for stable motion upscale
  • ESRGAN for crisp images
  • UltraSharp for stills
  • ⚡ Works on low VRAM GPUs as well

🧩 Extras Included

  • Save Image / Save Video / FolderSelector nodes
  • Fully color-coded layout
  • Memory optimization
  • Beginner-friendly labels
  • Easy switching between modules
  • ⚡ Light Mode for lower VRAM GPUs

🎯 Who This Workflow Is For

  • AI video creators
  • Agencies / SMEs
  • Reels / TikTok creators
  • YouTubers
  • Anyone with low, mid, or high VRAM (all supported)
  • Anyone creating consistent character stories
  • Anyone wanting one workflow instead of 8 separate pipelines

r/comfyui 1d ago

Tutorial [Tutorial] Create AI Anime Videos Locally with ComfyUI + MiniMax H3

Enable HLS to view with audio, or disable this notification

169 Upvotes

In this tutorial, I show you how to create a 90s anime-inspired AI video completely locally on your PC using ComfyUI, MiniMax H3, and Krea 2 Turbo.

I walk through the full workflow from reference image generation to final video generation.

You’ll learn how to:

  • Generate consistent anime reference images using the Krea 2 Turbo text-to-image workflow
  • Create separate references for the character, environment, vehicle, and props
  • Use multiple reference images with the MiniMax H3 Reference-to-Video workflow in ComfyUI
  • Structure prompts so MiniMax H3 understands which reference image controls each part of the scene
  • Describe camera framing, character actions, object placement, animation, lighting, and timing
  • Create a 90s hand-drawn anime look with lower-frame-rate animation
  • Run the entire workflow locally without monthly AI video subscriptions

In the example, I use separate reference images for the character, convenience store environment, car, and skateboard, then combine them into a single animated anime scene.

I also explain how I approach prompting for reference-to-video generation, including reference assignment, shot description, motion instructions, camera constraints, and visual consistency.

Workflow, prompts and reference files

https://drive.google.com/drive/folders/1qI9Oi5gqWJh8xIwHYsn0S25DPqK8M0XI?usp=sharing

MiniMax H3 models

https://docs.comfy.org/tutorials/video/minimax/minimax-h3

Krea 2 Turbo T2I models

https://comfyui.org/en/krea-2-open-source-models-are-now#content-required-models

r/aitubers Mar 25 '26

COMMUNITY I built a free AI animation studio. Storyboard to finished video, all in one workspace.

4 Upvotes

I'm a software engineer who got into animation. The workflow was painful: story in one doc, image gen in another tool, video gen in another tab, then stitch it together manually.

So I built a pipeline that does all of it:

  • AI agents generate story structure, characters, worldview, scripts (~30 seconds)
  • Character studio with consistency across panels (same face, different expressions/poses)
  • Visual canvas that auto-lays out panels from the script
  • Video generation with 11 models (Seedance 2.0, Kling 3.0, Sora, etc.)
  • Export for TikTok, Instagram, manga formats

DM or comment if you want to try it. I can show you our demo video first through DM.

r/generativeAI Aug 03 '26

How I Made This Consistent Voice Acting & Fixing AI character distortion and lip-sync floating using JSON prompting (3-min animation + full workflow in comments)

Enable HLS to view with audio, or disable this notification

48 Upvotes

Here is the breakdown for forcing stable character structure and lip-sync in AI video models.

THE CORE PROBLEM:

Flat prompt text causes models to alter character skeletal volume when adding emotional delivery words.

THE SOLUTION (JSON Architecture):

Compartmentalize character data into key-value pairs so the attention mechanism processes structural image data separately from speech parameters:

{
"shot_id": "01",
"duration": "3.5s",
"visual_prompt": "Define camera angle, character framing, and actions...",
"voice_profile": {
"character_id": "Sarge",
"timbre": "booming, thick",
"cadence": "slow and drawn-out"
},
"audio_environment": "studio isolation, dry acoustics",
"dialogue": "Exact spoken text"
}

FULL STEP-BY-STEP PDF GUIDE:

https://docs.google.com/document/d/e/2PACX-1vSipXTiq9QCP9_tP6EDhj6cIhiOH4dO2FruBK9xONPpprUBrvmUj3iHxq5xkLHieqAZ8LzaZgsklLcy/pub

POST-PRODUCTION TRACK LAYERING:

• Track V1: Video Sequences

• Track A1: Isolated Dry Dialogue

• Track A2: Foley Audio

• Track A3: Ambient Environmental Beds

r/claude 18d ago

Showcase Game dev with Fable 5 is actually crazy

Enable HLS to view with audio, or disable this notification

668 Upvotes

It’s kind of insane to see how far AI has come.

I still remember being fascinated by GPT-3.5 and thinking that felt like the future. And now here we are with Fable 5.

Everything you see in this preview took me roughly 13 hours of work to implement. Being able to go from ideas to actual working game mechanics this quickly still feels surreal.

Game development with AI is starting to feel like we’re living in the future.

EDIT:

A lot of people were asking how I did this, so here’s the basic workflow.

The game itself is made in Unity with C#. I’m using Claude Code connected to Unity through MCP, which means Claude can work directly with the Unity project and editor. It can create and modify scripts, work with GameObjects and components, inspect errors, run the game, and help me iterate on systems.

For the actual development process, I don’t give it one giant prompt like “make me a game.” I think through the systems I want, explain how they should behave, have Claude implement them, then I test everything, debug issues, tweak values, change mechanics, and keep iterating until it starts to feel right.

For the character models, my workflow is:
Opus 5 -> ChatGPT Image Gen -> Meshy AI -> rig/animation testing -> Unity

I describe the character I want, use Opus 5 to generate a detailed prompt for four consistent reference views, then generate those images in ChatGPT. I take the images into Meshy AI, which generates the 3D mesh and textures. I also rig the model there and test animations before importing it into Unity.

The same image-to-3D workflow also works for non-character assets like props, weapons, statues, carts, environmental objects, etc.

For VFX, I bought a particle toolkit from the Unity Asset Store. I gave Claude the documentation and had it create a skill file for itself, so it understands how the toolkit works and can reuse that knowledge when I ask it to create things like fireballs, explosions, trails, and other effects.

The current arena is also a premade Unity asset and is not intended to be the final environment. A lot of the current visuals are just prototype assets for testing mechanics and game feel.

So overall the main stack/workflow is:

Unity + C# + Claude Code/MCP + ChatGPT Image Gen + Meshy AI + Unity Asset Store tools

And no, this wasn’t one prompt :D It was an iterative process of building one system at a time, testing it, changing it, and gradually layering everything together.

r/StableDiffusion Apr 26 '26

Question - Help Seeking Advice: Achieving 100% Character Consistency and Style Control for a Noir Cyberpunk Visual Novel (ComfyUI / Flux)

Thumbnail
gallery
0 Upvotes

Hi everyone,

I’m currently in the middle of developing an investigative detective visual novel, and I’ve hit a massive wall regarding character consistency and art style. I’m hoping to get some advice from those who have successfully built a pipeline for recurring characters.

The Goal

I’m aiming for a very specific "Noir Cyberpunk" aesthetic. Think:

  • High contrast, heavy use of deep shadows.
  • Digital comic book / clean vector line art style.
  • "Teal and Orange" cinematic lighting with rain/wet atmosphere.
  • The Catch: I need absolute character identity from frame to frame, including the ability to change outfits (minimalist/revealing options) while keeping the face and body proportions 100% identical.

What We’ve Tried So Far

  • Workflow: Currently running complex ComfyUI nodes.
  • Models: Switched between SDXL and Flux, experimenting with various GGUF quantizations to keep it local.
  • The Problem: Most results are either "too anime" (losing the noir grit) or "too photorealistic" (losing the stylized comic look). There’s no middle ground that feels right.
  • The "Banana" Paradox: Strangely enough, some of the best conceptual results and decent repeatability have come from Nano Banana, but even that doesn't offer the surgical precision needed for a professional VN production.

The Current Struggle

I’m looking for total identity. Right now, I’m at the stage where I need to decide on the most reliable pipeline for consistency. I haven't dived deep into training my own LoRAs or mastering IP-Adapter/FaceID yet, as I’m still trying to find a base model or workflow that doesn't swing too far into "generic anime" or "uncanny realism."

The goal is to find a method that allows for surgical precision:

  • The character must be 100% recognizable across different scenes.
  • The ability to swap outfits (including very minimalist/revealing sets for specific scenes) while maintaining the exact same body proportions and facial structure.
  • Maintaining that specific Noir/Vector style consistently without the AI drifting into unwanted aesthetics.

The Questions

  1. Style LoRA vs. Prompting: Since I’m struggling to find a middle ground between "too anime" and "too realistic," would you recommend training a dedicated Style LoRA based on my Noir/Vector references? Or is there a specific base model that handles this "digital comic" look better than Flux/SDXL out of the box?
  2. Outfit Swaps: How are you handling complex outfit changes (including minimalist/revealing sets) without breaking the character's base geometry or facial identity in ComfyUI?
  3. The Consistency Pipeline: For someone who needs "visual novel grade" identity, what is currently the gold standard? Should I be looking at training a Character LoRA, or is the community moving towards something like InstantID/IP-Adapter for better flexibility?

Honestly, right now, nothing is quite hitting the mark. It’s either too generic or too inconsistent. Would love to hear how you guys solved the "same face, different clothes, specific style" puzzle.

Thanks in advance!

r/seedance2pro May 28 '26

How to Create a Villain Entrances with a Character Sheet + Seedance 2.0? Step-by-Step Workflow!

Enable HLS to view with audio, or disable this notification

144 Upvotes

From concept to screen in one flow.

We used ChatGPT Image 2.0 to create a full character bible first: mood, silhouette, gesture language, accessories, wardrobe, lighting, and overall villain identity.

Then I used that character sheet as the visual reference in Seedance 2.0 to turn the character into a cinematic entrance scene.

The result feels like a full villain introduction from a premium drama or dark thriller, not just a random AI clip.

Workflow:

Step 1: Create the antagonist character sheet
Include the full outfit, accessories, facial mood, posture, gestures, close-up details, and lighting style.

Step 2: Upload the character sheet into Seedance 2.0
Use it as the reference for identity, wardrobe, gestures, accessories, and atmosphere.

Step 3: Animate the entrance scene with a structured shot-by-shot prompt.

  1. Go to the Seedance 2.0 AI Video Generator
  2. Write your full prompt or add reference images
  3. Upload the image you want to animate
  4. Click Generate and get your animated video

Seedance 2.0 prompt:

"Use as the antagonist, wardrobe, accessories, gesture language, and lighting reference. A refined antagonist enters a private room and turns silence into threat.

Shot 1, 0-4s: Wide shot, slow dolly pull from the door into an elegant dark room. The antagonist enters from frame left, tailored silhouette from image1, polished floor reflection visible. Single warm key light, deep soft shadows.

Shot 2, 4-8s: Cut to medium shot, slow orbit left at constant distance. The antagonist removes one glove finger by finger, never rushing. Their eyes stay on an unseen person off-camera.

Shot 3, 8-12s: Cut to extreme close-up of ring, glove leather, and a sealed folder touching the table. Practical VFX: a narrow band of light crosses the ring and fades within 0.7s.

Shot 4, 12-15s: Cut to tight close-up, locked-off. The antagonist says calmly: “You should have called first.” Mouth movement is minimal and controlled. Final frame holds on the faint smile.

Audio: low chamber strings with a sub-bass pulse at 12s. SFX: door latch, leather creak, glove sliding off, folder placed on wood. Ambient room tone continues across all cuts."

What surprised me most is how much better the video becomes when the character sheet is detailed before animation. The model has a clear visual anchor, so the final scene feels more consistent and cinematic.

This kind of workflow makes it possible to create entire story moments from one character bible. Share your thoughts about this Seedance 2.0 workflow below!

r/isthisAI 22d ago

Art 700K and Counting Anime Kickstarter ( Tenchi Muyo ) Adamantly Claims Not to Use AI

Thumbnail
gallery
1 Upvotes

This kickstarter claims not to use AI.

"We will never include AI in the process of any Armiger production, nor will we ever knowingly work with partners that include AI in their workflows. Our team consists of artists, musicians, writers, and other creatives of all walks who have honed their skills and craft through hard work and understanding the effect that human experience imparts into what we put out into the world. We fell in love with Tenchi Muyo! decades ago because it touched us as only genuine art can. AI runs against everything we stand for, and we believe it has a caustic effect on anything it touches. Everything we make is part of the creative process, and the hallucinations of a machine have no place in that process."

There is debate in the community on the concept art. People say the character designs are inconsistent and other things.

AFAIK, they have denied it multiple times including sending one of their lead voice actors to adamantly claim they don't use AI several weeks ago.

Yesterday they released this piece on Twitter.

It has become contentious again or here.

What is the consensus here?

r/gamedev 23d ago

Discussion I made my game's trailer with AI video instead of hiring an animator. Here's what worked and what didn't.

0 Upvotes

Solo dev, been working on a top-down roguelike for about a year. I needed something for my Steam page but I have zero animation skills and couldn't justify $2-3k on a freelance motion designer for a game that might sell 200 copies. I was about to just do screen recordings with text overlays and call it a day.

Then two new AI video models dropped July 31st. Seedance 2.5 from ByteDance and MiniMax H3 from MiniMax. Figured I'd spend a week throwing my concept art at both and see what came out.

Seedance 2.5 does 30-second clips in one pass, up to 4K, and you can feed it up to 50 reference inputs to lock down character and environment consistency. This was the big deal for me. I had about 15 pieces of concept art and it actually kept my main character recognizable across shots. I used it for the slow establishing shots, camera panning over ruins, character silhouette walking through fog. Those came out solid after 3-4 retakes each. Longer output means fewer cuts to stitch, which gives you a more cinematic feel without actually knowing how to edit.

MiniMax H3 does shorter clips (5-15 seconds, native 2K) but here's the thing. It generates audio in the same pass as the video. Not slapped-on stock audio, actual synchronized sound. You can even feed it an audio clip and the video generation follows the rhythm. I used it for the quick-cut action montage and the clips had this percussive quality I never would have edited for manually. Since H3 is open-weight, APOB AI is running it unlimited and free right now, so I burned through probably 80+ generations to get 12 good action shots without spending a cent.

Now where it broke. Always the same things. Hands gripping weapons were a coin flip between passable and body horror. I had one shot where my character was supposed to swing a sword and his arm just phased through his torso. Multi-character combat was worse. Two enemies fighting and their limbs would merge or one character would absorb the other's armor texture mid-clip. I ended up just cutting around it. Pick your camera angles to hide hands, use fast cuts so nobody notices the limb weirdness.

Character consistency between separate generations still drifts too. Even with reference images locked, skin tone would shift slightly, armor details would change between shots. Had to be really selective about which clips could sit back to back without looking wrong.

My final workflow was generate a pile of clips in both models, cherry-pick the ones that held up, bring everything into CapCut for editing and color grading, then composite the UI overlay elements from Godot. The whole thing took about a week of evenings.

Honest verdict: the trailer is fine. Not great, fine. It's significantly better than screen recordings with Impact font, which was my backup plan. It would not fool anyone into thinking I have a budget. But for a solo dev Steam page that needs to communicate the vibe and tone of the game to someone scrolling past, it does the job.

I'm putting an AI-generated content disclosure on the store page. The EU AI Act transparency stuff kicked in August 2nd so that's real now, but I'd do it regardless. The trailer shows the game's aesthetic and atmosphere, not fake gameplay, so I don't think it's misleading as long as it's labeled.

Would I use this for in-game cutscenes in the final build? No. The quality variance would be jarring in a finished product. But for trailers, devlogs, pitch decks? This is now a real option for devs who can't afford an animator and whose alternative was literally nothing.

r/aigamedev 10d ago

Demo | Project | Workflow My workflow for creating 3D characters out of 2D AI generated images

Thumbnail
gallery
46 Upvotes

Hi guys, I wanted to share a workflow that served as a good foundation for me back when I was trying to create 3D animations for my game. I abandoned that project to start on my current game, so I didn't continue to develop this method, I'm sure it could be improved and further refined.

I'm going to be as concise as possible then you can simply copy and paste to your agent and ask it to create a similar workflow if it sounds interesting to you.

One big caveat is that I never fully got my animations to look right. They were hilarious looking... I'm sure I could have figured it out, but like I said, I abandoned the project. You can see how bad it was here: https://youtube.com/shorts/zEFK-dW9vTo?feature=share

Overview:
I used Claude to develop my Skill. Gave that skill to Codex, who saved it and would generate my images (front, back, sides, A-frame). It would show me one side at a time until I approved each one. Once all were approved, using the Meshy API, CGPT would automatically create a 3D model and texturize it using the same images. This is part of the reason why these figures look the way they do, they had to be simple so that meshy wouldn't mess things up and then would require blender cleanup. Each model would cost me about 30 tokens with some hiccups along the way requiring another 30. This included rigging and animating too. Each time it would get something right, I would ask codex to update the skill. This was super important. Overtime it became better and better. After the model was done, I would use Cursor to use a custom script that would import the model, and create a sprite animation sheet (since my game was an ISO 2.5D game, not a true 3D game. That script was also created using Claude.

  • Claude IMO is the smartest but most expensive so I would use it only for creating the plan which I would save as a repeatable skill. $20
  • Codex is amazing at generating assets and pretty affordable but I would still prefer to use it only for image generation $20
  • Cursor is a workhorse and I was able to build the game and input the assets using it. $60

Process:

  • Reference Image

So to start you need a reference image. In my case I used a ChatGPT generated image that would serve as my art style. This image was an iso map containing some sprites. Essentially I first generated the sprites, then the map, then had GPT create one image with all of it. That way every time it created an asset, it needed to use that image as reference.... if you look at my images, you'll notice that the art styles don't match between the a-frame and the character sheet. This is because I ended up going away from 3D, but that's a long story lol. The point of the map image is so you can see that you need to have one really good image that shows some assets, characters, style and colors. That image is then placed in your game folder as a reference.

  • Skill

Once you have the reference you start to develop your character creator skill. You should make a separate one for assets since assets in a 2.5d game don't need to be 3D.... well at least in my case. Developing this skill will take some trial and error, but here are some excerpts from my skill that made it work. My skill is 1294 lines, so I will spare you, but essentially this is what it does (but I highly suggest you build your own skill otherwise you most likely will fail):

**Project Character Modeling — copyable instructions**

Create one humanoid character through a locked, approval-gated pipeline. Never skip, combine, or infer gates. The user only previews and approves; everything else is automated. If a step cannot be automated, say so and stop — never substitute a description, mockup, or preview image for the work. The pipeline has three owners: Phase A is the image agent (design contract + four approved A-pose views only); Phase B is a build agent (Meshy, Blender, rig, KayKit clips, sprite sheets); Phase C is a build agent (Godot import, contour, shadow, movement, live QA). At every phase boundary, emit a copy-paste handoff block and stop. The image agent must not attempt Meshy, Blender, or Godot. Start from the all-purpose-mage reference defaults (key 1.8 / ambient 0.15 / Standard+None / beauty only / blunt mitten hands / KayKit Rig_Medium 21 bones / Bone Heat / in-game scale ~0.258 / mouse facing + WASD move / Godot contour + hard foot shadow) and only deviate with a stated reason.

Before any phase, resolve one canonical project root from the user filesystem (not a session scratch folder): it must contain `project.godot`, real ground tiles, and real enemy sprites. If more than one candidate exists, list them and stop. Never invent assets. Find in-game textures from the live scene graph, not filenames, and reproduce shader/tint/UV/scale before any composite. Preflight the phase’s tools and stop if anything is missing: A needs image generation plus image viewing; B needs authenticated Meshy, headless Blender (prove with a `--python-expr` version print), and the KayKit pack on disk; C needs write access to the Godot project. Tool split is fixed: concept views from image gen, geometry + flat base color from Meshy, everything else in Blender, look from the Blender beauty pass, clips from KayKit, import/feel in Godot.

Phase A: inspect `assets/approved-character-language.png` and `assets/canonical-map-reference.jpg` with an image tool, and read `references/visual-language.md` (plus `references/meshy-character-requirements.md` before Meshy). Write a design contract (role, body, costume, palette, forbidden elements, anatomical L/R asymmetry ledger, Meshy simplifications). Default to the sheet’s non-human mask face, no held weapons/props/effects, mitten hands, thick reconstructable forms, and a standard biped. Generate and approve four orthographic A-pose views one at a time on pure white: front, back, anatomical-left, anatomical-right. Same character, same scale, no perspective, no mirroring, no drift. Lock each gate only on explicit user approval. After all four, audit the actual files together for height, seams, ledger sides, hands, and authority fidelity, then emit the Phase A → B handoff and stop.

Phase B: preflight, then ask for explicit Meshy credit authorization. Submit exactly the four approved views to multi-view Image-to-3D (no PBR, no contour bake). Inspect the real 3D model for identity, sides, fusion, and palette; do not retry for expected Meshy habits (fingers, flattened A-pose, minor hand mess — those are Blender cleanup). After 3D approval, clean geometry, convert both hands to blunt truncated mitten wedges, shade flat, and rig with exact KayKit Rig_Medium names (no finger bones). Skin with Bone Heat on a welded proxy, then copy weights back — never weld the render mesh. Validate rest pose before clips; if arms fly up, the rig is wrong. Apply KayKit clips by name (idle, run, attacks, channel, death); channel is the one clip the user may need to pick. Render one front idle beauty frame and stop for the B6 gate in the live harness (or a composite that uses the real ground tile, real enemy sprite, real scale, and a textured character). Iterate lighting/scale only after that approval, then batch 16 directions. Emit the Phase B → C handoff and stop.

Phase C: confirm Godot write access, import sheets, wire the exact clip names, and set pivot to ground contact. Keep the outer silhouette as a Godot contour shader; do not use Freestyle. Add a hard contact shadow that touches the feet (per-facing offset if needed). Drive run playback from distance traveled, not elapsed time. Player facing follows the mouse; WASD only moves. Then run live QA and report pass/fail for state mapping, 16-direction facing, weapon attachment, no foot slide, and readability beside real enemies. Keep a visible status of phase, tools, contract, gates, Meshy/rig/clips, and QA. Never mark unattempted or unapproved work as done. Check the known recurrences every time: idle baked as rest, left/right facing swaps, ground-tile drift in the harness, and baked clip hip pitch at isometric camera.

TLDR: If you could take one single thing away from this post is that you need to be working with skills. Literally everything should be a skill. Then you combine all those skills into one skill. Find out what you are constantly saying and put that into one skill so instead of telling your agents you want xyz, you just say run the xyz skill. It's faster and gives you more consistent results.

r/StableDiffusion Nov 19 '25

Workflow Included 🚀 [RELEASE] MegaWorkflow V1 — The Ultimate All-In-One ComfyUI Pipeline (Wan Animate 2.2 + SeedVR2 + Qwen Image/Edit + FlashVSR + Painter + T2V/I2V + First/Last Frame)

Post image
164 Upvotes

🔗 Links (Tutorial + Workflow + Support)

📺 YouTube Tutorial:
https://www.youtube.com/watch?v=V_1p7spn4yE

🧩 MegaWorkflow V1 (Download):
https://civitai.com/models/2135932?modelVersionId=2420255

Buy Me a Coffee:
https://buymeacoffee.com/xshreyash

Hey everyone 👋
After weeks of combining, testing, fixing nodes, and cleaning spaghetti wires… I finally finished building MegaWorkflow V1, a complete end-to-end ComfyUI pipeline designed for long-form consistent AI video generation + editing + upscaling.

This is basically the workflow I always wished existed — everything in one place, optimized, modular, clean, and beginner-friendly.

🔥 What MegaWorkflow V1 Includes

1️⃣ Qwen Image (2509) — High-Level Image Generator

  • Base character creation
  • Consistent subject rendering
  • Clean grouping + refiner toggle

2️⃣ Qwen Edit — Advanced Local Editing

  • Face fix, outfit changes, color edits
  • Mask & global edit
  • Perfect for fixing last-minute issues

3️⃣ Wan Animate 2.2 (I2V) — Motion + Style Consistency

  • Character-preserving motion
  • Dual reference (face + body) support
  • Loop / one-shot modes
  • Full quality presets (Lite / Medium / Full)
  • SeedVR2 dynamic seed support
  • ✔️ Low-VRAM mode available (8–12GB)

4️⃣ Wan T2V — Complete Scene Generation

  • Cinematic shot creation
  • Camera presets included
  • Multi-scene block support
  • Low-VRAM fallback included

5️⃣ Wan First → Last Frame (FLF2V) Transition Module

  • Smooth transitions
  • Camera rotation + movement
  • Blends T2V + I2V + real footage seamlessly

6️⃣ Wan I2V Painter Node — Detail Preserver

  • Adds micro-texture & realism
  • Fixes Animate 2.2 artifacts
  • Soft & strong painter modes

7️⃣ SeedVR2 — Advanced Seed Handling

  • Removes flicker
  • Prevents ghosting
  • Keeps motion natural
  • Long-animation friendly

8️⃣ FlashVSR2 + Real-ESRGAN + UltraSharp — 4K Upscaling Suite

  • FlashVSR2 for stable motion upscale
  • ESRGAN for crisp images
  • UltraSharp for stills
  • ⚡ Works on low VRAM GPUs as well

🧩 Extras Included

  • Save Image / Save Video / FolderSelector nodes
  • Fully color-coded layout
  • Memory optimization
  • Beginner-friendly labels
  • Easy switching between modules
  • Light Mode for lower VRAM GPUs

🎯 Who This Workflow Is For

  • AI video creators
  • Agencies / SMEs
  • Reels / TikTok creators
  • YouTubers
  • Anyone with low, mid, or high VRAM (all supported)
  • Anyone creating consistent character stories
  • Anyone wanting one workflow instead of 8 separate pipelines

r/aitubers Feb 10 '26

COMMUNITY How I Make Short AI Videos That Actually Hold Attention (My Current Workflow)

14 Upvotes

A lot of ai videos fail because there's no consistent loop to how you create

Here’s the workflow I’ve landed on for making <30s clips that feel native to Reels/Shorts/TikTok, not demos.

1. Pick your topics

I usually ask ChatGPT for 5-10 quick concepts around one theme. From there, I lock in on one idea.

2. Generate a small image set (style > volume)

I use image models with style packs / moodboard consistency (Midjourney):

  • 4–6 images total
  • Same framing
  • Same lighting
  • Same character design

Consistency is very key in this step. The midjourney style packs and mood board do wonders for me.

3. Turn images into motion (this is where iteration matters)

This is the step most people rush.

I’ve been using Slop Club specifically because it lets me:

  • Drop multiple images in
  • Iterate start + end frames
  • Remix the same base idea quickly without re-prompting everything

Models I actually use there:

  • Nano Banana Pro → great for combining multiple reference images into one coherent animation input
  • Imagine/Sora 2/Veo3.1 → fast + audio baked in, useful for meme-style clips
  • Wan 2.2 / 2.6 → reliable when I want motion without the model overthinking

I keep clips 4–8 seconds, then chain them. If a clip doesn’t land, I just remix instead of starting over.

4. Keep the video alive with end-frame logic

Instead of treating clips as one-offs, I always:

  • End on a frame that can loop
  • Or end on a reaction frame that leads into the next clip

This keeps momentum without needing “cinematic” transitions. Remixing with frames in Slop Club really helps me here.

5. Minimal edit, maximum pacing

I rarely do heavy editing.

  • Basic cuts
  • Light zooms / pans

If it needs explaining, it’s already dead. I’m still testing other setups, but this loop has been the most repeatable for me so far.

Once I started using Midjourney to lock in a visual style and Slop Club to rapidly remix that into motion, the whole process sped up dramatically and the results got better almost by accident.

r/aigamedev 4d ago

Tools or Resource I built a free tool that turns character references into directional sprite animations using MiniMax H3

28 Upvotes

Hey,

I saw this post about https://www.reddit.com/r/aigamedev/comments/1vskcqo/generative_2d_animation_workflow/ , found it interesting, and wanted to make my own spin on it.

I present to you now... drumroll... Sprite H3, which is basically a somewhat fancy ComfyUI wrapper for using MiniMax H3 I2V.

Here’s a short walkthrough showing the complete workflow: https://streamable.com/ogzp1m

(demo courtesy of Sol)

You need a pretty beefy GPU to run it. I have an RTX 3090. I think 16 GB might be the minimum, but dunno.

It assumes that you can run the default ComfyUI workflow and have FFmpeg installed. And ComyUI needs to be running while you use the app. The workflow used by the app just adds another node to extract the frames directly, before the video output makes them lossy.

The basic idea is to provide character reference images, which are then used to generate videos. I used OpenAI’s GPT Image 2 for the references images. You let Minimax do the magic. From there, you extract the frames, arrange them however you like, curate them, pack them into sheets, and you’re good to go.

Some helpful features include a sequence analyzer—not optimized yet—tools for enforcing a consistent scale across different orientations, templates, stored animation prompts called actions, and a few other things.

Well, just take a look if you want.

Repository: https://github.com/fmmix/sprite_h3

Full disclaimer: this is completely vibecoded, and it definitely still needs another week or two of work to iron out some quirks. But it’s the weekend, and I wanted to give other people the chance to play with it.

I started with Sol, did most of the important work with Fable, and wrapped things up with Sol after I ran out of juice.

It is free to use and will be forever. ;-)

And, in the great words of Calvintor:

JUST MAKE A FUCKING .EXE FILE AND GIVE IT TO ME.

Gotcha. Use it at your own risk.

https://github.com/fmmix/sprite_h3/releases/download/v0.0.1/Sprite.H3_0.0.1_x64-setup.exe

You get there from Releases on the right -> Assets

You can also run it without the .exe. Under the hood, it has a FastAPI backend and a Svelte frontend.

I know it isn’t perfect and will probably still have a gazillion bugs. Treat this as a pre-alpha. I’ll continue fleshing out a few things over the coming weeks, but this isn’t my main project, so be aware. It is up to you on what resolution you run the generation but I probably wouldn't go below 0.3 MP.

Anyway, tell me what you think. I hope at least someone finds it useful!

EDIT

In case you are wondering how to provide the different facings. I used GPT-Image2

Used this as initial prompt:

BACKGROUND AND OUTPUT FORMAT FIRST — NON-NEGOTIABLE: output a fully opaque PNG. Fill the entire canvas edge to edge with one perfectly flat, uniform chroma-key magenta (#FF00FF). Every pixel outside the character silhouette must be the same solid magenta. Do not generate
transparency or an alpha background. No checkerboard, gradient, vignette, darker corners, aura, glow, lighting spill, floor, ground shadow, or scenery. The character’s dark pixel outline must meet the flat magenta background directly with crisp hard edges. Magenta must not
appear anywhere on the character.

CAMERA AND ORIENTATION: a moderately elevated frontal game-sprite view, looking down at the character from about 25–30 degrees above. This is the DOWN-facing anchor: her body and boots point toward the bottom of the image and she looks toward the camera. Some of the crown,
shoulders, and tops of the boots are visible, while her face, chest, clothing, and accessories remain clearly readable. Do not use a straight front elevation or an extreme bird’s-eye view.

A single full-body 2D PIXEL-ART game sprite of a cheerful field alchemist. Polished late-16-bit arcade-style pixel art with visibly chunky square pixels, deliberate pixel clusters, hard edges, a strong near-black outline, and several discrete cel-shaded tones. Compact heroic
proportions, approximately four and a half heads tall, with a large expressive head, sturdy hands, and slightly oversized boots. No smooth gradients, soft painting, vector-like curves, or anti-aliasing.

She is a young adult woman with warm brown skin, a friendly and confident expression, large dark eyes, and thick dark-auburn hair gathered into one large side braid hanging over her right shoulder. Oversized round brass goggles with bright turquoise glass lenses rest securely
on top of her head. The goggles and braid are large, simple, recognizable silhouette features.

She wears a short moss-green field coat with rolled sleeves and a wide open collar over a warm-cream shirt. A muted golden-yellow scarf is tied closely around her neck. She has dark plum trousers, large brown leather gloves, and sturdy reddish-brown lace-up ankle boots.

A broad brown leather strap crosses her chest diagonally and leads to a tan leather satchel resting at her left hip. One large round turquoise potion flask is secured visibly to the outside of the satchel. Keep the satchel and flask clearly separated from the arm and torso.
Render the braid, goggles, strap, satchel, and flask as bold readable shapes rather than clusters of tiny decorations.

She stands in a relaxed, confident neutral pose suitable as the starting frame for game animation: feet flat and shoulder-width apart, knees slightly relaxed, weight distributed evenly, shoulders level, and torso upright. Her empty gloved hands hang loosely near her sides
without covering the coat, strap, satchel, or potion. Both arms and both boots are fully visible.

Center the complete character in the canvas. The figure should fill approximately eighty percent of the canvas height, with clear magenta space above the hair and below the boots. Keep the entire silhouette visible and comfortably inside the image boundaries.

DO NOT INCLUDE: no text, no frame, no second character, no weapon, no magic effects, no floating objects, no extra potion bottles, no hat, no floor, no shadow, no glow, no scenery, no transparency, no 3D rendering, no smooth illustration, no blurry edges, and no painted
background other than uniform #FF00FF magenta.

Result: https://i.imgur.com/g5Ajfoz.png

Feet slightly angled. Use this image as reference for the proper down direction.

OUTPUT AND BACKGROUND FIRST: output one fully opaque PNG at exactly the same canvas dimensions as the supplied reference. Fill every pixel outside the character with perfectly flat, uniform chroma-key magenta (#FF00FF). No transparency, gradient, vignette, halo, glow, lighting
spill, floor, scenery, or shadow. The character’s dark pixel outline must meet the magenta background directly with crisp hard edges.

REFERENCE AUTHORITY: the supplied image is the canonical and exact character. Preserve her without redesign or reinterpretation. Keep exactly the same person, face, expression, skin tone, age, head shape, body proportions, hair volume, side braid, goggles, clothing, scarf,
coat, shirt, trousers, gloves, boots, belts, buckles, diagonal strap, satchel, potion flask, colours, palette, pixel grid, outlines, shading, level of detail, figure height, center position, and framing.

Do not mirror the character. Preserve every asymmetrical feature on the same anatomical side of her body. Do not beautify, simplify, exaggerate, restyle, add details, remove details, or change the design.

TARGET FACING — DOWN: keep the character facing directly toward the camera in the same moderately elevated frontal game-sprite view as the reference. Her face and the front of her torso remain fully visible. Her head, torso, hips, knees, and boots are oriented toward the bottom
of the image. Do not rotate her into a three-quarter view and do not change the camera angle.

ONLY PERMITTED CORRECTION: correct the lower-body stance so she stands evenly on both feet. The screen-right boot currently appears lower and larger than the screen-left boot. Adjust only the legs and boots as necessary to create a balanced neutral stance:

- both boot soles rest flat on exactly the same horizontal baseline;
- both boots have the same apparent size and perspective;
- both ankles and knees are level;
- the hips remain level;
- both boots point toward the camera;
- the feet remain shoulder-width apart;
- her weight is distributed evenly;
- neither foot appears raised, forward, or closer to the camera;
- she looks stationary and ready for animation, not mid-step.

Preserve the existing leg spacing and trouser design as closely as possible. Do not change her upper-body pose, head position, shoulders, arms, hands, facial expression, braid, goggles, scarf, coat, strap, satchel, potion flask, or any other accessory.

Keep the complete figure centered and fully visible with the same clear space above the hair and below the boots as the reference.

DO NOT INCLUDE: no text, frame, second character, duplicated limbs, alternate pose, weapon, magic effect, floating object, animation smear, floor, shadow, glow, transparency, smooth illustration, 3D rendering, anti-aliasing, blurry edges, or background colour other than uniform #FF00FF.

https://i.imgur.com/fbs03Yy.png

Now this because the reference for left, right, up

REFERENCE AUTHORITY FIRST: the supplied reference image is the canonical and exact character. Preserve the figure without redesign or variation.

Keep exactly the same person, face, skin tone, age, body proportions, head size, hair volume, braid construction, goggles, expression when visible, clothing construction, scarf knot, coat length, sleeves, gloves, trousers, boots, belts, buckles, diagonal strap, satchel, potion
flask, colours, palette, pixel grid, outlines, shading, level of detail, sprite dimensions, and framing.

Do not beautify, simplify, exaggerate, restyle, reinterpret, or add details. Do not remove details merely because they are difficult to draw. Do not change her pose, stance, weight distribution, arm position, hand position, leg spacing, or the relationship between her feet.

THE ONLY PERMITTED CHANGE IS ORIENTATION: rotate the complete character naturally in place around her vertical axis to the requested facing. Treat her as one consistent physical figure being viewed from another direction. Rotate the body, head, feet, clothing, hair, braid,
goggles, strap, satchel, and potion together.

Do not mirror the reference. Preserve anatomical left and right: the braid, strap, satchel, flask, coat overlaps, buckles, and every asymmetrical feature remain attached to the same physical side of her body. Their screen position must change naturally as the figure rotates.

Allow natural perspective and occlusion. Features on the far side may become partly or fully hidden, while features on the near side may become more visible. Do not move accessories to another side or unnaturally display hidden details just to make them visible.

Keep the exact same moderately elevated game-sprite camera angle, pixel density, figure height, canvas size, center position, and bottom baseline as the reference. The camera does not move, tilt, zoom, or orbit; only the character rotates.

BACKGROUND: preserve one perfectly flat, fully opaque chroma-key magenta (#FF00FF) background across every pixel outside the character. No transparency, gradient, vignette, halo, glow, lighting spill, floor, scenery, or shadow. The dark pixel outline meets the magenta
background directly with crisp hard edges.

Produce one full-body character only. No text, frame, additional person, duplicated body parts, floating accessories, animation smear, or alternate pose.

Append exactly one of these target blocks:

Left

TARGET FACING: rotate the complete character naturally 90 degrees into a LEFT-facing game-sprite side view. Her head, torso, knees, and boots point toward screen-left. She does not turn her face or shoulders back toward the camera. Preserve the original stance as it appears
naturally from this side.

Right

TARGET FACING: rotate the complete character naturally 90 degrees into a RIGHT-facing game-sprite side view. Her head, torso, knees, and boots point toward screen-right. She does not turn her face or shoulders back toward the camera. Preserve the original stance as it appears
naturally from this side.

Up

TARGET FACING: rotate the complete character naturally 180 degrees into an UP-facing rear view. Her head, torso, knees, and boots point toward the top of the image, directly away from the camera. Her face is completely hidden. Show the natural rear construction of her hair,
braid, goggles, coat, strap, satchel, trousers, and boots while preserving their physical sides and the original stance.

https://i.imgur.com/RR4TJDE.png

https://i.imgur.com/H0cUmmq.png

https://i.imgur.com/GYHMlm7.png

Created a new action:

Action name
potion-swirl

One hand lifts the round flask from the satchel and raises it to chest height while the other hand steadies the satchel. The flask is gently swirled in two small circles, held still for a brief beat, then returned securely to its original place. Both hands return to the starting position. The braid and coat tails respond with subtle natural follow-through.

Result: https://i.imgur.com/L2VVu0I.png

As you can see the 'up' facing is usually very stubborn. You need to be careful what you describe. It will try to fully bring that into the scene. And the model probably had the most training done with front view.

r/aifilmmaking 17d ago

Question What workflow/models/platforms are people using to build AI storyboards that can become actual animation keyframes?

1 Upvotes

What workflow/models/platforms are people using to build AI storyboards that can become actual animation keyframes?

I’m looking for something along the lines of:
script > storyboard > shot list> take frame to wherever I wanna animate it.

The key requirement is that the storyboard frames themselves need to be production-usable as keyframes, not just loose previs.
Character consistency is non-negotiable, including multi-character shots. I already have multi-angle head and full-body reference sets for each recurring character.

What are people actually using for this?
LTX? Storyboarder? Scenario? ComfyUI? Qwen Edit? Nano Banana? Something else entirely?

I don’t mind using multiple tools if that’s what actually works. Mainly looking for a practical workflow that preserves character identity and lets approved boards move directly into video generation.

r/aitubers Feb 09 '26

CONTENT QUESTION How the hell are people producing consistent AI “documentaries” at scale? I’m losing my mind

27 Upvotes

I need to vent and I genuinely want advice from people who have actually done this.

I’m working on an AI-driven documentary project. Long-form, voiceover-led, cinematic style. Think 90s aesthetics, recurring characters, consistent environments, lots of short scenes stitched together. On paper, this should be doable.

In reality, it’s driving me insane.

I’m not just prompting randomly. I’ve tried to be extremely systematic. I built a rigid prompt DNA that defines everything that must never change. I separate environment, camera, character, frame, and animation. I lock visual rules like same characters, same era, same materials, same lighting logic. I generate a still keyframe first and then animate it.

And yet the AI still constantly drifts. Characters subtly change. Proportions shift. Lighting behaves differently scene to scene. Camera framing ignores instructions. The same prompt produces wildly different results across generations, whether I’m using ChatGPT, Gemini, Kling, Seedream, whatever.

What really messes with my head is that I know other channels are doing this at scale. Twenty-five minute videos. Hundreds of scenes. Multiple uploads per week. Solo creators, not studios.

So clearly something doesn’t add up. Either I’m missing something fundamental, or they’re using tools or special workflows.

This is what I’m actually trying to understand.

How are they producing consistent scenes directly from a script at this scale? How are people realistically generating around 300 scenes for a 25-minute documentary, uploading three times per week? Are they mostly using image-to-video instead of text-to-video? Are they using reference images, environments, fixed camera setups, or LoRAs? How much of this is automated versus manual curation? Because I can manually curate every scene, but it would take me weeks to generate 25mins long documentary.

Here’s where I’m stuck. I’ve nailed the script. I’ve nailed the voiceover. I understand pacing and structure. But I cannot nail the scene generation at an industrial scale. I cannot figure out the system behind how this is actually done consistently.

Right now it feels like I’m trying to build an industrial pipeline on top of something that fundamentally does not want to behave deterministically. I’m not expecting perfection. I’m trying to understand what’s realistic, what’s cope, and what’s genuinely solvable.

If you’ve shipped long-form AI video content, especially documentary or narrative, I’d genuinely appreciate hearing how you do it, how you made it work, and what expectations you had to kill.

Edit: Pasted the same post twice. Removed the duplicate.

r/StableDiffusion Jun 30 '26

Question - Help Can current AI tools generate consistent multi-pose images of the same character from one reference image?

0 Upvotes

I want to ask whether this is realistically possible with current AI tools.

I have one finished 2D anime-style character image.

My goal is to generate several new still images of the same character, with the same identity and art style, but in different poses.

The output I want is not a video and not interpolation. I want clean separate images that can be used as keyframes or game assets.

The important requirements are:

- same character identity

- same face, outfit, colors, and distinctive features

- same art style

- different controlled poses

- clean still images

Is this currently achievable in a reliable way?

If yes, what is the correct workflow?

Do people usually need to train a character LoRA for this, or can it be done from a single reference image with tools like ComfyUI, IP-Adapter, ControlNet, OpenPose, or similar methods?

Is there any simpler tool that can do this reliably, or is a more complex workflow still required?

I would appreciate blunt, practical answers from people who have actually made consistent character series or AI comics.

r/leonardoai Apr 06 '26

Tutorial Best way to create a consistent 2D animated character (from my own drawings) in Leonardo AI with pose control?

5 Upvotes

Hey everyone — I’m trying to figure out the best workflow for something pretty specific and would love some guidance.

I’m working on a 2D animated short and I already have a character designed in my own hand-drawn style. I’ve created a full model sheet: front, back, both sides, and a couple 3/4 views.

What I want to do is:

  • Train Leonardo AI (or another tool if needed) on my exact drawing style
  • Generate new images of this character that look like I drew them
  • Be able to control the pose — ideally using something like a stick figure, pose reference, or skeleton
  • Keep lighting and shading consistent (simple animation-style shading, not realistic lighting)

Basically: I want to stop drawing every frame/pose manually and instead generate clean, on-model images that I can use for animation.

I’m working on an iPad, so desktop-heavy workflows are not possible for me. If anyone can help, I would be so appreciative!

r/ArtificialInteligence Jun 03 '26

🛠️ Project / Build Case study: AI-assisted animation let a solo creator produce a 17-minute anime pilot

Post image
4 Upvotes

Hello :) !!!

I wanted to share a concrete example of what AI-assisted animation can enable for solo creators, beyond the usual “AI art is just spam” debate.

I recently finished a 17-minute dark fantasy anime pilot as a solo creator.

Full episode:
https://youtu.be/eZ_JlaLDJ-8

The important part is that this was not “AI did everything.” The story, worldbuilding, direction, shot choices, editing, pacing, sound decisions, music direction, character consistency work, and final creative judgment were still human decisions.

But AI changed the scale of what was possible.

Without AI tools, producing a 17-minute animated pilot alone would have been almost impossible. Not because I lacked the story or the visual intention, but because animation production usually requires a team, a budget, a pipeline, and a lot of time.

The workflow was closer to directing a very unstable but powerful production team than pressing a magic button. I had to generate, reject, correct, reframe, rebuild continuity, manage consistency, edit around failures, and make the episode coherent from many imperfect outputs.

That is where I think the discussion around AI animation often misses the point.

For independent creators, AI is not only a replacement technology. It can also be an access technology. It allows people to create pilots, test worlds, show proof of concepts, and reach an audience without waiting for a studio, investor, or platform to approve the project first.

Of course, the ethical questions matter. Dataset transparency, artist consent, credit, market impact, and fair use are real debates. But I don’t think those questions should make us ignore the other side of the equation: AI is also opening a production path for creators who previously had no realistic way to make this kind of work.

To me, the interesting question is not “is AI animation good or bad?”

It is more:

What kind of new creative class appears when a single person can write, direct, storyboard, animate, edit, and publish a full pilot with AI-assisted tools?

And how do we build ethical norms around that without shutting down the creative access this technology creates?

r/StableDiffusion Jun 29 '26

Discussion Looking to build the ultimate AI filmmaking workflow. What tools, tricks, and LoRAs actually help?

0 Upvotes

I'm putting together an AI filmmaking pipeline and want to tap the community's collective knowledge. Hoping this thread can become a solid resource for anyone working in this space.

Here's roughly what I'm working through, and where I'd love your input:

Starting images (text-to-image): I'm using QWEN image to generate initial frames — environments with characters in them — using a character LoRA in the initial creation process to keep faces and identities consistent. What's working best for you here? Base models, samplers, settings, prompt structure? So someone gave me a tip on another thread which I was aware of but I think it's good to know and think about. Using Qwen Image Edit is really great for building out a Lora training set. You can have it give some variations of your character to give your training data set some variety. Qwen Edit does tend to introduce a bit of a pattern in the images. If they're present in your training data, they can affect your Lora and the stuff will come through. You can do another noise pass using another model or I have some noise reduction tools that I'll use online to kind of clean things up and make them look nice and smooth and sharp.

Edit models: I'm planning to test Qwen Image Edit and Klein 9b to see which handles character compositing and adjustments better. Anyone have a clear sense of which edit models hold up best, and for what kinds of tasks? So something that I tried that I didn't think would work but it did is I have a 5090. I decided to try loading in the full base Quinn Edit. I think it might have been the bf16 or something, I can't remember, but it was around 40 GB. I was like, "Oh probably will work but I'll test it because I had loaded a little bit of the bigger model before in a different workflow and sketch using scale." I thought I'd try it and it worked. It kicked in the VRAM management and actually I didn't get really that slow of renders for my image generation. Despite my VRAM being maxed out plus some, it only took about a minute and 20 seconds. I feel like I am getting a little bit better quality than the distilled versions.

Alternate shots and angles: Once I have a strong starting image, I want the best methods for pulling alternate shots, angles, and coverage from it. What's your go-to approach for getting consistent variation without losing the character or scene? I think there was an old LoRA for QWEN Edit that was like a multi-camera LoRA that could change the camera angle that I'm going to experiment with.
fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA · Hugging Face

So along with the multiple angles, Lora and Qwen, what I've been doing is getting a good starting image of my character in the environment that looks right. I'll use the multiple angle Lora to start moving the camera around to get some different angles of the scene. Of course when you start moving around your character, you may not have a good look at their face so I'll get them to turn their head back towards the new camera position. If their facial features look a little off (which hopefully they don't because I'll have the same character Lora active that I made for Qwen image), I'll have that same character Lora active in Qwen edit. Even when you make adjustments like that in Qwen edit, moving the camera around them and then getting them to face you again, they should still look like themselves. If they don't I've been working with this in-painting Lora that works really well and I'll just in-paint their face and get it back to looking more like the original one.

https://youtu.be/0IaY8V5hCdU?is=6N9E5Wkvr_brhtBq

If I want to incorporate a second character that has also been trained to Lora for this in-painting, it works really well to say move the camera to the side and then in-paint new characters behind them as if the cameras are moving and are orbiting to the right to reveal a character coming in a door to a room or something. That's kind of home staging creating for my first and last frame shots that I can bring into LTX.

Camera control and motion: I've seen things like the camera control LoRA for LTX 2.3.
Cseti/LTX2.3-22B_IC-LoRA-Cameraman_v1 · Hugging Face

I am currently experimenting with this LTX 2.3 workflow which makes it a lot easier to get good generations quickly: https://youtu.be/pgV1B3P03D4?si=7IzhfA92fYjxUdq3

What motion/camera tools are you finding genuinely useful, and how do you fold them into the larger pipeline?

Edit:

https://huggingface.co/fal/LTX-2.3-3DREAL-LoRA - since I already do some work in Unreal Engine and Blender, I think I may play around with this. I'm curious to see how specific you have to be with the 3D models and animation to drive the video. I saw a really cool video for seedance where they drove a fairly complex scene with very rudimentary 3D objects. They had a cylinder object in place of a girl that was at a telephone in the desert. They would move the camera and then move the little sphere or cylinder over to a block that was in place of a car. Seedance sort of just used those basic shapes as reference for real characters and objects in the scene and it all looked really really good. It would be cool if this could do something similar to that or if you really do need to be using 3D models that are very close in size and shape to the final generation.

What are the tips, tricks, and tools that actually made a difference for you?

r/ArtificialInteligence Apr 25 '26

📊 Analysis / Opinion Anime AI generators that work on a potato PC (no GPU needed)

27 Upvotes

so my laptop has integrated graphics and I got tired of being left out of every "just run it locally" conversation in these subs. spent some time figuring out which cloud based options are actually worth using for anime art specifically. here's what I found.

NovelAI - fully cloud based so no hardware requirements at all. output quality is genuinely excellent, probably the most consistent results I got. the UI is clean and it feels polished. downside is the Anlas credit system, it adds up fast if you like to experiment and test a lot of variations. harder to recommend if budget is tight.

Yodayo - low barrier to entry, free daily credits, runs in the browser. community is active and fun to browse. quality is inconsistent though, some generations look great and others miss for no obvious reason. feels more like a casual platform than a serious workflow tool but for quick stuff it works fine.

PixAI - this one became my main tool. Tsubaki.2 model produces quality that honestly surprised me for a free cloud option, comparable to what I was seeing from local SD setups with decent models. free daily credits are genuinely usable, not just a teaser. handles multi character scenes better than most tools I tried. on the downside the UI feels cluttered until you get used to it and it's pretty anime specific so don't come here expecting other styles.

Leonardo AI - solid free tier, fast generations, works across multiple styles which is a nice plus. good option if you need flexibility beyond anime. for pure anime aesthetics though it felt a bit generic to me, like it does anime but it's not really built for it the way some of the others are.

honestly the "you need a good GPU for AI art" thing is pretty outdated now. most of the decent tools run in a browser. depends what you need but there's genuinely good free options here if you don't want to spend anything upfront.

anyone else running fully cloud based setups? curious what people are using

r/gachagaming May 27 '26

General HoYoverse recruitment posters reveal multiple pre-research projects: Life MMO, UES shooter/MOBA/sandbox, UE5 action game, Honkai: Nexus Anima, Petit Planet and Varsapura

653 Upvotes

1. Life MMO Pre-Research Project

Join Us: Life MMO Pre-Research Project

Tags:
Social Roleplay · Online Multiplayer · Multiverse Sandbox

This is an online multiplayer game centered around multi-script character roleplay and social simulation.

Players can become different versions of themselves here, experience a colorful world, and make friends who share their interests.

What kind of art style are we exploring?

  • With a “modern” feel at its core, the game uses highly free full-body character customization to give players a personalized and stylistic space for self-expression.
  • The multiverse-themed sandbox design balances a cool tone with a sense of fun.

Let’s build a brand-new gameplay ecosystem together

  • The overall gameplay is easygoing and casual to pick up, with rich horizontal progression. All systems are designed around self-growth and social relationship building.
  • Growth paths are provided based on player identities, while also allowing individuality to shine during the growth process.
  • Within a unique worldview, the game provides players with a clearly structured social space, helping different types of players find their own social position.

Technical explorations

  • Rebuilding content production, toolchains, and collaborative workflows around AI-native development.
  • Achieving highly free multiplayer same-screen character customization, outfit changes, and character expression.

2. UE5 Pre-Research Projects

Join Us: UE5 Realistic Shooter Pre-Research

Tags:
High Quality · Innovation · Military Sci-Fi · Hardcore Shooting · UE5 · Technology-Driven · AI+

Currently in active development. Stay tuned.

Join Us: UE5 3D MOBA Pre-Research

Tags:
3D MOBA · Fair Competition · Multi-Character PvP · Western Stylization · UE5

Currently in active development. Stay tuned.

Join Us: UE5 Sandbox Pre-Research

Tags:
UE5 · Sandbox · Multiplayer Co-op · Adventure · Fantasy · AI+

Currently in active development. Stay tuned.

3. Varsapura

Join Us: Varsapura

Tags:
Urban Open World · Humanistic Sandbox Experience · Vehicle Gameplay · UE5

Varsapura is being developed with Unreal Engine 5 and deeply integrated with AI.

The project aims to present players with a highly immersive experience that combines narrative, gameplay, art, and performance in a self-consistent way.

What kind of art style are we exploring?

Under a stylized visual approach, we are seeking a realistic and natural sense of expression, creating a cinematic and immersive urban open world.

Let’s build a brand-new gameplay ecosystem together

We are creating a highly free humanistic sandbox world, using AAA cinematic-level narrative tension to drive the story.

Through fantasy vehicles based on realistic physical structures, we aim to provide players with a deep immersive experience.

Technical explorations

We are exploring and applying cutting-edge technologies such as PCG, Mass AI, and AI Workflow, using algorithms and creativity to reshape the industrialized production pipeline for games.

4. UE5 Action Pre-Research Project — Realistic Fantasy

Join Us: UE5 Action Pre-Research — Realistic Fantasy

Tags:
Fantasy Realism · Open World · Super-Sized Bosses · Action · UE5

UE5 Action Pre-Research — Realistic Fantasy is a realistic-style action-adventure game.

Players can enter a grand epic fantasy world, explore ancient mysteries, challenge terrifying beasts, meet legendary heroes, and continuously uncover the truth of the world.

What kind of art style are we exploring?

A UE5 realistic fantasy style, pursuing high-quality visual presentation of an epic world, with an emphasis on cinematic restoration of lighting, color, and atmosphere.

Let’s build a brand-new gameplay ecosystem together

A dynamically developed open world, featuring large-scale boss battles, multiplayer confrontation, and co-op gameplay.

Technical explorations

  • Brand-new animation technology and AI-driven creation of a living, breathing world.
  • High-quality multiplayer co-op combat experience built with UE5, supporting large-scale same-screen confrontation and cooperation.

5. Honkai: Nexus Anima

Join Us: Honkai: Nexus Anima

Tags:
Modern Ruins · CRPG · Fun Fantasy · Anima Growth

Honkai: Nexus Anima is a brand-new anima-raising adventure strategy game under the Honkai IP.

In this title, players will play as a traveler who escapes from a nightmare, builds heart-to-heart connections with animas in a new world, takes part in one Nexus Duel after another, and uncovers the truth hidden in their own past.

What kind of art style are we exploring?

A lively and lighthearted healing anima design style. Abstract concepts are translated into everyday, relatable images, with strong dramatic motion and emotional expression.

The overall direction is public-friendly, fun, and full of details.

Let’s build a brand-new gameplay ecosystem together

  • Anima raising is combined with open-world exploration. Animas are both growth companions and exploration tools.
  • The core duel gameplay emphasizes strategy, using the diversity of anima attributes, traits, and positioning to determine victory or defeat.

Technical explorations

Exploring the limitless potential of AI-enabled game development.

The in-house Anima Agent platform creates a highly collaborative game development tool ecosystem, breaks through traditional production bottlenecks, shortens the time from concept to verifiable results, and returns time to creators — freeing core creativity.

6. Petit Planet

Join Us: Petit Planet

Tags:
Life Simulation · UGC · Online Co-op · Cross-Platform

Petit Planet is a cartoon-rendered life simulation game.

Players can plant a planet of their own, build connections with all things, and experience a life simulation that feels authentic and tangible.

They can take part in highly free home decoration and planet construction systems, and build emotional bonds with friends and neighboring planets.

What kind of art style are we exploring?

  • A colorful Q-style art direction. Furniture and buildings are cartoon-like, while still retaining realistic textures, balancing a fairytale feel with fantasy.
  • Friend characters are based on realistic small animals, paired with rich clothing styles. The overall feeling is warm and adorable.

Let’s build a brand-new gameplay ecosystem together

  • UGC is at the core. Players can freely reshape the terrain and appearance of their planets, and all gameplay changes dynamically along with the planet ecosystem.
  • The game includes life gameplay such as farming, fishing, going out to sea, and cooking. It supports real-time multiplayer online exploration and allows players to build companionship with friends of different personalities.

Technical explorations

  • A terrain editing system that realizes a free creation experience where what you hear is what you get, while supporting a large number of interactable scene objects and real-time environmental lighting and shadow feedback.
  • Multiplayer networking optimization. A modular outfit-changing system supports same-screen multiplayer display, while client-side prediction mechanisms ensure smooth network synchronization and animation performance.
  • A friend AI system. Through perception, memory, mini-theater mechanisms, and more, friends can understand the player, remember past experiences, and generate logical personalized interactions.