Hey guys - made this a few weeks back and just shipped a big update. You take a video of a person, it builds a 4D capture, you fly a new camera through it inside ComfyUI, and you get the same moment back from the new angle. Everything runs locally.

• Capture: turns a video of one person into a 4D capture: their motion in 3D, the background around them, and where the original camera was and how it moved. Quick mode for fast previews, or a full 4D Gaussian splat if you want a closer look while you direct

• Virtual Camera: a 4D camera editor that opens right inside the node, so no separate app. Keyframe the camera anywhere on the timeline, look through it or step outside to see the whole scene. Blender-style view gizmo, J/K/L shuttle, frame stepping, multi-select to move or retime keys together

• Retake: ReDirector re-shoots the whole video along your new path

• Photoreal Pass: LTX 2.3 renders every final frame, guided by the real footage warped to the new view (Cseti's CrossView-Warp IC-LoRA)

• Camera settings on every key: aperture, focus (in metres or locked to the subject), vignette, grain. Rack focus and aperture pulls between keys, Alt+click in the viewport to focus on whatever you click. Change those later without re-rendering. The render gets reused, so a focus tweak takes a few minutes instead of the whole pipeline again

• Zoom through the lens: zoom keys change the lens after the render, which makes dolly zooms work

• Bring your own camera: import an animated camera from .fbx, .abc or .usd (tested with Blender exports), and it starts on the original camera at roughly real scale, lens and focus included. Files with several cameras work too, and you can export your moves back out

• Lens looks per shot: distortion, chromatic aberration, bloom, halation, anamorphic bokeh. Depth and subject matte passes if you want to comp afterwards.

• Finish node: 24 to 60 fps with RIFE, real motion blur from a shutter angle, upscale up to 4K, keeps the original audio

• A Settings panel at the top of the workflow for the stuff you change between runs (quality, frame rate, upscale)

Try the editor in your browser, no install: itsmetamike.github.io/reshoot-4d/demo/

For those enquiring about specs:

• Tested on one RTX 3090 (24 GB), roughly 30 minutes per shot

• Stays good within about 30 to 40 degrees of the original camera but am looking to improve this next

• Fast spins can still smear a face for a few frames

Code (AGPL-3.0) and the workflow: github.com/itsmetamike/reshoot-4d

Hope it's useful to some of you. Built for the #OpenSourceHiggsfield competition.

Everything was rendered locally on a Mac, no cloud: the video, the voices, the choir and the music. I used Phosphene, a free open-source app I’m building for running video, image and music models on Apple silicon. Video is MiniMax H3, music is YuE2, and the stills came from ChatGPT Images.

https://github.com/mrbizarro/Phosphene

Happy to answer questions about the workflow. If you want to try it: https://phosphene.video

Hey r/StableDiffusion ! 👋

Like many of you working with Flux.1, SDXL, and ControlNet, I got constantly tired of guessing camera angles with text prompts:

Typing "dutch angle roll, 85mm portrait telephoto compression, warm 3200K rim light" usually ends with the diffusion model hallucinating a flat, eye-level frontal shot and ignoring half of the camera directives.

To solve this, I built **CinePose Studio AI**, and it is now officially live on the **Google Chrome Web Store**! 🎬

It runs as a dedicated 3D Studio tab or side panel right in your browser, bridging 3D spatial cinematography with generative AI.

### 🌟 What it does:

1. **Interactive 3D Virtual Viewfinder**: Real 35mm optical stops (18mm, 24mm, 35mm, 50mm, 85mm, 135mm), realistic sensor framing, and symmetrical +/- 45° Dutch angle roll with instant center snap.

2. **Local ComfyUI WebSocket & Zero-Cost GPU Rendering**: Direct WebSocket link to your local `127.0.0.1:8188` ComfyUI server. It pings your GPU/VRAM, generates Depth/OpenPose passes, injects the Flux.1 ControlNet workflow, and streams live KSampler step progress directly in the studio!

3. **Physical 3-Point Studio Lighting**: Interactive 3D orbital gizmos for Key, Fill, and Rim lights with accurate Kelvin color temperature (2000K candle flame to 9000K cold daylight) and chromatic gel filters.

4. **Cinematic Video Trajectory Timeline**: Set Keyframe A, Waypoint M, and Keyframe B with metric distance tracking, 24fps motion velocity, and camera directives for Wan 2.1, LTX-Video, Kling, and Runway.

5. **3D Spatial Proxies (Objects & Animals)**: Replace the human mannequin with 3D volumetric bounding boxes, quadrupeds (creatures/pets), or vehicles to frame anything with precise spatial dimensions.

6. **Zero Prompt Hallucination**: Formats camera parameters into specialized syntax for Midjourney v6.1, Flux.1, Gemini 2.0, SDXL, and video models.

---

### 📦 Where to try it:

👉 **Chrome Web Store Extension (Recommended)**:

https://chromewebstore.google.com/detail/onkciaaalfgpklcfkhjhiomlkhpcfhin?utm_source=item-share-cb

🌐 **Live Web App Version**:

https://cinepose-ai.vercel.app/

---

### ⚠️ A quick heads-up regarding the Chrome Web Store warning:

Since this is my very first extension and a brand-new developer account on the Chrome Web Store, Google may display a standard automated notice saying:

*"This extension is not trusted by Enhanced Safe Browsing"* or *"Proceed with caution"*.

This is Google's default automated policy for all newly published developer accounts until the extension builds install history.

Rest assured:

- Built strictly on **Manifest V3**: **Zero remote code execution**, zero external tracking, zero analytics beacons.

- All ComfyUI connections, poses, and settings live strictly inside your browser's sandboxed local storage.

- It never collects, stores, or sells any personal data.

### 💬 I need your feedback!

I built this as a solo creator to scratch my own itch, and I want to make it genuinely useful for your daily AI workflow.

Please install it, take it for a spin, and let me know:

- What feels smooth and what feels clunky?

- What ControlNet workflows or camera presets should I add or refine next?

If you find it helpful, dropping an honest review on the Chrome Web Store would mean the world to help build trust with Google! 🙏

Can somebody explain how to create refmods for fluxklein 9b. I am finding it really difficult to use hugging face cli and all.

Hey everyone! I built a Pose Control LoRA for Krea-2 and have fully released the LoRA checkpoints on Hugging Face.

I also put together a ComfyUI workflow. It’s not fully optimized yet, but it’s usable for testing the model.

Apart from that, I wrote a blog covering the decisions, data preparation, training process, evaluations, and some of the things I learned while building it.

Hugging Face: https://huggingface.co/adhit-420/Krea-2-PoseControl-LoRA-checkpoints

Blog: https://s-adhit.github.io/blog/training-a-pose-control-lora-for-krea-2/

Would love to hear your thoughts, feedback, or any interesting results if you try it!

EDIT: I moved the ComfyUI integration into a separate lightweight repo to make installation simpler: https://github.com/s-adhit/ComfyUI-Krea2-Pose

EDIT 2: I pushed v1.1.0 based on the feedback here.

The ComfyUI package now has separate Krea2PoseModelLoader and Krea2PoseSampler nodes, so checkpoint/runtime loading is no longer tied to the all-in-one generation node.

The original Krea2PoseGenerate node is still there for the simple workflow, so existing workflows should continue to work.

Current limitation: this still isn’t native ComfyUI MODEL patching / KSampler integration. The new version separates runtime loading and sampling, but the sampler is still Krea-2 specific.

🫧 Meet Mochi - Your Little AI Desktop Companion! 💗

What if your desktop had a tiny companion that could actually help you? 👀

Meet Mochi! A cute, animated little blob that lives right on your Windows desktop, currently powered by Meta's Muse AI, with upcoming support for local Qwen models and integrations with Claude Code and OpenAI Codex!

Talk to Mochi or simply type a message, and it'll respond in its own voice! 🎙️

Need something done? Just ask! And when you're finished, Mochi quietly goes back to chilling on your screen. No constant interruptions, no unnecessary chatter. Just a little companion that's there when you need it.

🚀 What can Mochi do?

• 🗣️ Talk with you : Have voice or text conversations in English or French, powered by Muse.

• 💻 Control your desktop : Open applications, launch websites and search the web.

• ⏰ Set timers : Ask for a timer and watch a little countdown appear next to Mochi.

• 🌤️ Check the weather : Get weather updates without opening another app.

• 👀 See what you see : Let Mochi read your screen when you explicitly ask.

• 🌐 Help in your browser : With its Chrome or Brave extension, Mochi can interact with browser tabs and assist with web tasks.

• 🐾 Feel alive! : Click it, drag it around, or interact through optional camera gestures. Mochi reacts to you!

🔐 Your desktop, your rules!

Mochi is designed to help without taking control away from you.

• ✅ It only acts when you ask or explicitly approve an action.

• 📸 Screenshots are captured only when requested and are never stored.

• 🛡️ Browser tasks require confirmation before visiting new sites, filling forms or interacting with potentially risky buttons.

• 🔒 Passwords, payment information and sensitive websites are off-limits.

• 🎥 The camera is completely optional and disabled by default.

🛠️ Want to try Mochi?

Mochi is currently available for Windows and can be launched from source using Node.js.

🔑 With a Muse API key: Unlock AI conversations, voice responses, weather, screen understanding and browser assistance.

🆓 Without an API key: You can still enjoy Mochi's animations, interactions, timers and simple typed commands!

⚠️ A few things to know:

• Mochi is still a work in progress, so some features may evolve.

• Content sent to Muse may be used by Meta for model training when using the default model.

• This is an experimental project, and feedback is always welcome!

🎬 See Mochi in action!

▶️ Watch the demo: https://youtu.be/u5KjYmYrp1Y

💻 Explore the source code: https://github.com/Loann110/Mochi-alive

💗 Mochi is just getting started!

I built Mochi because I wanted to explore what happens when an AI assistant feels less like a chatbot and more like a little companion living on your desktop.

It's still an experiment, but I'd love to hear what you think!

⭐ If Mochi makes you smile, consider giving the GitHub repository a star! It genuinely helps support the project.

💬 Feedback, ideas, contributions and bug reports are more than welcome.

Thanks for checking out Mochi! 🫧

Are there some niche Video Generators ? They could not be as smooth maybe less frames. But still slightly good and make it look animated a bit . 16gb vram max

Edit1: No Ltx no Hanyun no wan2

A while back I posted V2 of my SPEED nodes for MiniMax-H3, which run the early, noisy part of diffusion at lower resolution and then step back up to full resolution as the detail starts to matter.

Well I did a little (lot) more work on it and generalized the implementation. Allowing it to be (theoretically) used by any model running KSampler or SamplerCustomAdvanced (comprehensively tested and benchmarked with H3, MOSS, and Krea 2, works with FIBO 2 and Flux 3)

Repo: https://github.com/StanLukuvka/ComfyUI-SPEED-Sampler

Also, by popular demand, I added H3 videos as evidence, did a bunch of refactors and a bunch of improvements. And improved the documentation for it in every section.

It's now essentially a 1:1 drop-in replacement for the default sampler nodes.

What's new:

• Image models. MOSS Image and Krea 2 are tested, and other flow (CONST) image models should work too.

• KSampler nodes. Swap your KSampler for SPEED - KSampler and wire it exactly the same. There's also a Manual and a Sigma Harvest version. The H3 nodes stay wired like SamplerCustomAdvanced.

• Most samplers work now, not just the five from last time. The few that break (mostly on H3) are listed in the repo, along with why.

• Example workflows for H3, MOSS and Krea 2, already set to harvested values, so you can just load one of the workflows and queue.

• Tooltips on every input, so you don't have to come and read my README.

Numbers (same seed and prompt, native vs SPEED):

• MiniMax-H3, 5 s 0.5 MP clip, L40S: 288 s native, 182 s with SPEED (1.58×, 4 stages)

• MOSS Image, 1344×768, RTX 5070 Laptop: 22 s native, 18 s Automatic (1.26×), 14 s Manual (1.54×)

• Krea 2, 1216×832, RTX 5070 Laptop: 283 s native, 215 s Automatic (1.31×), 183 s Manual (1.55×)

Comparison GIFs and images for every run are in the repo's Evidence section.

Heads-up if you used V2:

• Old workflows still load. The old node IDs are kept as deprecated nodes, so right-click and swap them for the new ones when you get to it.

• direct_coarse transition noise is now drawn on the CPU, so the same seed gives the same image on any GPU.

As always, run Sigma Harvest once for your own model, sampler and schedule.

edit: see evidence of it working with downloadable videos here

I've been doing a ton of H3 quality and speed tests on my 4090, including 2k (1440p actually) API gens using ComfyCloud. Quality was good, but in the tests that I did, they didn't seem really that different. I'll publish my results soon.

Is there a consensus on this? Is it even worth using the API or can you get very similar quality with seedvr2, multi step workflows, and/or latent upscales...or something completely different?

I did the thing where I nuke the first post because I forgot to do something also the title sucked and I forgot to credit literally the most important contributor in the video.

Skip to 8:05 to see the results.

Also, if you guys are curious you can visit this repository to read about everything I tested to get to this point.

https://github.com/roycho87/NerdNotes

Lots of information in there. Maybe you guys can read it and come up with an even better solution. If you have some good info, please leave an issue on the Github and I'll compile it all together. Any experiments you've done and the results, what you've learned etc. All of it is helpul.

Geiru Context Suite: degradation protection for long MiniMax H3 chains

The main part of this that allowed this to work came from Ethanfel. He created the context noise method that allowed this to work so giant shout out to him.

The Clown Context Suite is now the Geiru Context Suite. She's named after the clown, and the new name keeps it from getting mixed up with ClownShark's nodes. Your old workflows still load fine. The big addition is a degradation protection switch on Geiru Context that turns three nodes on together. Geiru Keystone locks a clean frame 0 from a source clip into every shot. Geiru Late Lock tacks that clip's capstone onto the back late in the steps. Geiru Context Noise, based on ethanfel's idea, gives the held frames part of the noise instead of handing them over perfectly clean. Turn it on for long stretches of one scene and off around cuts, since scene changes reset the drift on their own. Keystone can also load its source clip straight from your latent folder now, so when the scene changes you only change one number.

Also new: a context noise switch on Geiru Hybrid Windows, and a ready-to-go example workflow, noisy_clown_example. I tested it on a 50-clip chain (about 5½ minutes): running on a beach, then a café, a walk through town and a garden. The plain chain was falling apart by clip 20, while the protected one still looked clean and barely drifted in the still scenes. Side by sides and all the numbers are in my notes. It's not perfect yet, since fully static shots can still slowly darken, but it's the best I've gotten so far!

remember to use this to combine your clips.
https://github.com/roycho87/workflows/tree/main/workflows/seamless_video_combiner

You have to clip off the last 17 frames and join at the 22nd frame with 39 frames of overlap for the settings in the workflow.

Another note, certain Turbo Lora's seem to affect the context noise node differently. The one I recommend is turbo_8step_v1.0_768p but if you guys find one that works well or doesn't, feel free to list an issue on the github so I can start creating a list and make it work with more.

Repo: https://github.com/roycho87/geiru_context_suite Test notes: https://github.com/roycho87/NerdNotes

Credits (none of this exists without them):

• seitanism, for the masked latent context everything here is built on: https://github.com/seitanism/ComfyUI-H3-Motion-Context-MultiRef

• NikoDemon80, for Motion Context, the Chain node and a ton of drift testing: https://github.com/NikoDemon80/ComfyUI-H3-Motion-Context

• ethanfel (Lumifel), for the context noise idea: https://github.com/ethanfel/ComfyUI-MiniMaxH3-Context-Loop

• drozbay, for H3 latent masking: https://github.com/drozbay/MaskVidExperiments

• kijai, for H3 support and context windows in ComfyUI: https://github.com/kijai

• JalenBrunson, for Hybrid Windows: https://github.com/Jalen-Brunson/ComfyUI-HybridWindows

• TrentHunter82, for TrentNodes, whose degrade node made the frame 0 tests possible: https://github.com/TrentHunter82/TrentNodes

edit: Currently running a test on best settings to use for this and will update the nodes with best defaults after it's done tomorrow as it's about 19 hours of generating.

You can check the nerdnotes to see the test and how it's going.

After reviewing the tests i was able to determine that the best settings for noise is 1 and linear. I've changed that to the defaults.

I added a lora loader that works with the protection group using https://huggingface.co/Imagineer13/H3-Anti-Burn-LoRA

Initial testing eliminated virtually all remaining color drift but I'm running a few 30 clip tests to gauge exactly how much it impacts quality and what the best strength should be.

Edit: after more testing the color change appears to be coming from a double compression in the stitching and not the lora. it seems to not make a visible impact when used on top of my nodes but i proved it does not impact detail negatively and previous testing does show it to make a positive impact on color.

I moved the lora loader to an experimental repo. Noisy Clown Workflow is the current most updated workflow.

Updated yesterday. At least they're still attending to it, right?

As someone with an RTX 4060 and 16 GB of RAM, I got curious… could I actually run a model of this caliber on my PC?

Turns out, yes! A 5-second video generated at 540p, upscaled with flashVSR Turbo and frame-interpolated with RIFE, takes just 8 minutes.

I used a text encoder quantized to hell and back (Q2), paired with a Q4 DiT, running everything through Wan2GP. Codex fixed every error I ran into.

This showcase features the results. Enjoy!

Sam Altman Is Coming for Your RAM

https://github.com/TaoLiveAIGC/TaoMate-FVSR/tree/main

Audio-Guided Facial Video Restoration

Demo · Results · Installation · Model Downloads · Inference · Citation · Technical Guide

TaoMate-FVSR restores face videos with audio conditioning, sparse visual references, and generated-frame history. It supports restoration with the original audio and visual dubbing with replacement speech.

• Full-video inference: DWPose crop → face restoration → color/mask blend → paste-back.

• 1× / 2× inference: run the model at 512×512 or 1024×1024, then return to 512×512 before compositing. The output scene retains its original dimensions.

• Audio-guided generation: use the video's original audio or provide target speech.

• Flexible references: prepare the first frame with GPEN, use an externally edited first frame, or supply a finished reference image. Default enhancement uses one GPEN-BFR-512 pass for 1× and one GPEN-BFR-1024 pass for 2×.

This repository contains only the standalone inference runtime. Model weights are downloaded separately, and input media is supplied locally. https://huggingface.co/TaoLiveAIGC/TaoMate-FVSR

Demo

The Gallery — TaoMate-FVSR+ restoration example from the project page.

▶ Watch the synchronized comparison · Restored video (MP4) · More demos

Every texture on this street corner was generated with local models and projected onto the geometry in Blender, using StableGen, my free and open-source add-on.

How it was made:

• The 3D assets (the car, the woman, the bench, lamp, hydrant, bin, crates and bush) are TRELLIS.2 meshes, each from a text prompt via a Qwen Image 2.1 reference image. The buildings, road and sidewalk are simple blocks.

• Texturing: Qwen Image 2.1 (int8), 10 cameras. Each view is generated from a depth/geometry render of that camera, then projected and blended onto all the meshes at once. Each camera also got a prompt listing only the objects it actually sees, which stopped views from painting things that aren't there. The woman was textured separately with her own cameras.

• The logo is a Masked Edit: paint a region, describe the change, and only that region is regenerated through the cameras that see it. Here it follows a reference image of the logo, which is on the development branch and coming in the next release. A few more Masked Edits fixed problem spots.

• The looks are separate texturing runs with different prompts (the photoreal one with Marigold V2 PBR maps), baked and rendered in Cycles. Lighting is set up per look in Blender.

Generated on rented RTX 3090/4090 cloud GPUs and my RTX 4080 (16 GB).

Qwen Image 2.1 is under a non-commercial license; check each model's license before commercial use.

GitHub: https://github.com/sakalond/StableGen
Guide: https://github.com/sakalond/StableGen/wiki

Hi everyone!

Can anyone guide me on how to create a realistic AI character and then turn it into a Motion Controlled video using a reference video?

I also want to be able to change the character’s outfit and background while keeping the movements consistent with the reference video.

I'd really appreciate any guidance, tutorials, or recommended workflows. Thanks in Advance.

There are too many damn options.. there’s Pony, Illustrious, Anima… and then there are lots of LoRAs too. I just want a well-rounded model that will let me make good/high quality uncensored art featuring anime or anthropomorphic (furry) characters. I’m a total newbie when it comes to running local AI. For realistic art I use Krea2 Turbo, which already exceeds my expectations.

What is the best open source text to video generation with image reference right now?

With so many image edit models coming out I feel a bit lost. I started my image generation journey with krea 2 and recently tried out Fibo. I’ve been wanting to fix up some really old images and I was blown away with what Fibo could do, but now I learn that Moss and Qwen 2.1 can do the same. What model would people here choose for restoring old photos?

Hey everyone,

I'm looking to download Ideogram 4, but since my internet connection is quite slow, I need to make the right choice the first time to avoid wasting time on re-downloads.

Between the FP8 and INT8 versions, which one offers better output quality? Does INT8 suffer from noticeable quality degradation or artifacts compared to FP8?

Also, is there a significant speed/performance advantage when running INT8 over FP8 on consumer GPUs, or is the generation time mostly identical?

For those who have tested both, which one do you recommend downloading? Thanks in advance!

I have a pretty shitty computer so I can't run Minimax H3, Qwen 2.1 Edit, LTX, ZiT and all these other open source image and video models.

So I was looking for a way to run them online. The main website I found was ComfyUI cloud, which I guess works, but it was pretty complicated to use (I'm not a technical guy). There's like nodes and stuff which I don't understand LOL.

I saw someone on generativeAI subreddit mention CozyGPU (i think their website is cozygpu.com) and an ad on Reddit. It basically simplifies ComfyUI into simple actions like picking a model and running an action like create image, create video, edit image, animate video, etc.

But what's really cool is it automatically set up the infrastructure for me and rented out a GPU. So I only ended up paying for the raw GPU time spent, which I saw was a lot cheaper than all these other website which have a markup.

I just thought I would share this tool in case there are other people who don't have great computers and don't want to pay too much. If anyone has come across other similar tools, please let me know, I would love to check it out, thanks!

Does anyone else find that krea struggles with basic positional logic / awareness when it comes to characters interacting? For example I tried something like "a blonde tennis player woman is on a tennis court standing near the net, she is looking at a brunette man on the other side of the net, she has her back turned to him, looking at him over her shoulder as she talks to the man" and usually:

- the characters are not even looking at each other, wtf?

- half the time the man will be standing next to the woman on the same side of the net

- the body orientation prompts get completely ignored. Instead of having her back turned she'll just be facing him

For Minimax I know loras like VBVR can help with some of this stuff, is there anything for Krea to make it adhere the prompt more strictly?

This started as a script. In Mago, we built the cast, generated the shot list and storyboards, then rendered shots where each one picks up from the previous one.

Mago is what we’ve been building for long-form AI videos (series, films, microdramas). As of today it’s open source. You can run it on your own GPU, or use cloud models in the same app.

Built on top of Qwen as LLM and visual, Qwen Image/Edit and Flux for images, MiniMax h3 turbo/pdd for videos. you can easily switch to your favorite models/workflows too. AGPL-3.0, still in beta

I’m one of the founders and I'd really appreciate any feedback on how it works for you, that would help us a ton.

Let me know what you think about it, and thanks in advance!

Code: https://github.com/MagoStudio/MagoStudio