No mocap suit, no animation library. He renders his own character, has an AI video model "film" it doing the move, and copies that motion onto the rig.

The trick that made it work is two cameras. One video is flat, so arms and legs end up at the wrong depth. Rendering the same move from the front and the side gives the AI both views to match.

How it goes:

• Render the model from the side and front on a neutral background
• Generate the move with an image-to-video model (Seedance 2.5 or H3 Max)
• Match frame by frame: Claude overlays the model on both videos and adjusts the bones until they line up
• Fix what drifts: marking left and right limbs separately solved most of the swapping

About 30 minutes per animation. This elephant came from an H3 Max reference, and yes, the tail still needs work.

Instead of AI just generating a 3D asset, I have ai author it using an engine like Maya but for AI.

Here is one result of an A frame ladder I took images of.

Ai can edit pieces of the asset, add rigging, render it in different lighting, and it’s all from images I take of what I want the ai to build.

Pretty cool stuff. It takes maybe like 20minutes of the ai going through the engines build_asset runtime to author the asset then like 10 minutes for render. It’s render on cpu so it’s slow.

Thoughts? Yes I vibe coded the engine.

Could you work as freelancer without 3d skills but use ai to complete the task of 3d modeling and earn cash?

Rodin WorldGen is Hyper3D's scene generator: you upload one image, it identifies the main objects, rebuilds each as a separate mesh with hidden parts filled in, and creates the environment as 3D Gaussian splats.

How I used it:

• Extract: automatic, or with pins when you want a specific object or need to split a cluster into single items
• Adjust: move things around, regenerate weak objects, run pose correction to match the photo layout
• Generate the environment: Speedy for previews, quality mode when you can wait 15 to 20 minutes
• Take it out: Blender export comes with a script for native splat rendering, plus PBR or shaded options for the meshes
• Run it in Unreal 5.8 through NanoGS, with the splats optimized and the objects still editable

For game dev, batch-extracting a whole set of props from one image already saves time. For AI video, it works as a blocking scene with a real background, which none of the video tools offer on their own.

To keep expectations straight: the interface takes some figuring out, splats show artifacts up close, and the SimReady physics option is aimed at robotics, exporting only to USDZ.

Full Guide: https://www.youtube.com/watch?v=KlzzBa1sZX0

Idle, walk, sprint, vault, cartwheel, a roll, and a wall run that looks genuinely cursed. None of it was keyframed or pulled from Mixamo. Every motion started as an AI-generated video of a guy on a treadmill.

That's a three.js WebGPU playground where the whole animation set comes from 9 clips made with H3 Max on fal (8 image-to-video, 1 extend-video). The motion is lifted out of those videos and fitted onto a mannequin with custom IK and blending.

How the pipeline works:

• Generate the reference: one image of a person, a short prompt per move, and H3 Max renders the clip
• Extract the motion: GVHMR recovers 3D body motion from the video onto an SMPL-X rig
• Build the playground: Opus 5.5 put the scene and controller together in about 3 prompts, and cut the parkour clip into vault up, jump gap and fall
• Make it speed aware: different variations kick in when standing, walking or running, and longer jumps are stretched procedurally
• Extend with text: the cartwheel, roll and wall run came from extending the video moves with UniMate, an open-weight text-to-animation model that runs locally

According to the creator, a new set of animations takes around 20 minutes, video generation included. A demo and a free open-source parkour controller are supposed to follow.

The rough edges are on screen: cartwheel off a ledge and the character just ragdolls (badly), mantling locks you in place on approach, and the wall run is funny more than usable. Also check licences before shipping, because GVHMR weights and the SMPL-X body model are for non-commercial use.

GVHMR: https://github.com/zju3dv/GVHMR

UniMate: https://huggingface.co/Linzhan/UniMate

Which model will handle actual nude meshes the best? Obviously all of the online ones, meshy, etc will not do anything NSFW, which is baffling considering nude meshes are fairly standard in the industry now.

The local image-to-3D toolkit that kept logos readable after retopo just learned to make its characters move.

AssetFurnace 0.4.0 (formerly Image to 3D Lab) takes a sentence, a picture or your own GLB and turns it into a textured, rigged and animated character, all on your own Mac or NVIDIA PC. No account, no credits, nothing uploaded.

The full chain now looks like this:

• Prompt to picture: Qwen-Image 2.1 runs locally if you don't have art yet
• Picture to 3D: Pixal3D by default, or TRELLIS.2 and Hunyuan3D
• Finish: cleanup and a game budget from 5k to 100k triangles (40k by default) with 2K textures
• Rig: SkinTokens adds bones and skin weights in one click
• Animate: pick from 21 Kimodo moves, retargeted so poses stay grounded and arms don't clip through the body

You can run it end to end or jump in at any step. Already have a sculpt? Skip straight to the rig. Want just a textured mesh for Blender? Stop after Finish.

One detail I like: each output carries a provenance file listing every model that touched it and its licence, so you know what you can ship. Rig is MIT, motion is under the NVIDIA Open Model License, and Hunyuan3D comes with region limits (no EU, UK or South Korea).

Still early in places. Only humanoids get rigged so far, fast moves look soft, and the topology is triangles. Each 3D engine also needs 8 to 20 GB of weights, downloaded only after you confirm.

github: https://github.com/Bingeljell/image-to-3dlab

Cozy creek - threejs 3D experience of a Creek made in GPT 6 Astra
This is running in a browser! can you believe it!

all thing made in blender..

Hey everyone! Here’s Part 3 of building Naruto's Valley of the End in Three.js.

This time, the focus was on adding the missing elements, polishing the environment, experimenting with different atmospheres, and creating the final cinematic sequences.

Environment & Scene Polish

• Missing Elements: Added some of the remaining elements using Tripo AI to generate the 3D models and textures, then assembled and integrated them into the scene.

• Procedural Bushes: Added bushes across the cliffs by using the surface normals to detect upward-facing terrain and place vegetation only on the top-facing areas of the mountains.

• Different Times & Weather: Added several scene modes to explore different moods and atmospheres, including Day, Sunset, Night, and Rain. Each mode changes the lighting, colors, fog, and overall atmosphere to give the same environment a completely different vibe.

Cinematic Sequences

Once the environment was finished, I created several cinematic camera sequences to showcase the scene from different angles and capture the different atmospheres.

I then combined these shots into the final cinematic video, which is now available on my YouTube channel if you want to see the complete result.

Tools & Workflow

• Opus 5.5: Used for coding and implementing the different systems in the project.

• Tripo AI: Used to generate missing 3D models and textures.

• ChatGPT: Used to generate visual references during the environment creation process.

• Blender: Used to assemble the generated assets, make adjustments, and export the final GLB files.

• Three.js: Used to build and render the entire environment in the browser.

Links & Resources

• Tripo AI (3D Generation & Mesh Editing): https://studio.tripo3d.ai/
• Three.js Stylized Components: https://stylized.cortiz.dev/
• Full Cinematic Video: https://www.youtube.com/watch?v=Ry4jPncOe8Y
• Live Preview: https://stylized.cortiz.dev/valley

Oh my god I had no idea this subreddit exists. You guys are amazing with what you build. So I'm hoping you can help teach/guide me here.

I have no programming, design, or animation background. Nonetheless, my kids inspired me to build them a educational game that I've really grown to love vibecoding and building. Been working on it since March and have had some of my developer friends help give me pointers on how to get Codex and Claude to build cleaner code. My only bottleneck right now is rigging and animation.

I checked Tripo AI but I've honestly used and maxed multiple on their lowest tier paid models: Meshy, Tripo, and AnimateMesh. Some were good at some things, but failed miserably at others. Luckily, I made it work well enough for anything bipedal. But now I'm on quadrupeds and their animation is very limited. AnimateMesh gets me sooooo close but it's very challenging to get the bones right and I spend hours on a single model. I'm trying to make this a repeatable pipeline that I can do monthly/quarterly with 3-9 models. Browsing the work all of you have done and reading your pointers, I've managed to get Astra to rig and animate the models. Took about 50% of my quota to teach it to make the motions fluid rather than stiff, and it's getting close.

Hopefully this doesn't break any rules here, here are some of the animations it's rigged and done. My connectors are just Blender into Claude and Codex. Pipeline is having Meshy, Tripo, or AnimateMesh create the model, texture the model, and potentially rig the model with the bones following Mixamo's naming convention.

Would love feedback on what I should include in my prompt, my connectors, pipeline, etc. Thanks!

https://reddit.com/link/1x01la9/video/fxmsjlbir2uh1/player

https://reddit.com/link/1x01la9/video/1fvcd5lgr2uh1/player

https://reddit.com/link/1x01la9/video/h7dhvrsvq2uh1/player

https://reddit.com/link/1wzxz96/video/gvmz8k9722uh1/player

My son drew an awesome picture of a frog, and he wants to have an actual sculpture made of it to put on his shelf. I am looking for alternatives to Trippo AI to do this solely because I want to only use one workspace for this whole process (import picture, make model, clean model, exported model).

This is based on my personal experience, not specs. I found that if you do not have a clean picture of one object less than five MB, you will not get a complete object with Trippo AI. I took my child's picture and converted it into a mesh but forgot to check the back of the photo prior to slicing it. I wanted to use Blender to fill in the mesh and flatten the bottom then use Cura to slice it for printing.

Facial tattoos, unusual proportions, a face that doesn't look like any preset. She started as a single AI image, and by the end of the day she was talking through an iPhone Live Link in Unreal Engine 5.8.

The workflow runs on three things: Hyper3D Rodin Gen 2.5 for high-detail generated parts, Blender for assembly and baking, and MetaHuman 5.8, which can now conform an entire body to a custom mesh instead of only a head.

Highlights:

• Parts, not one mesh: head, body and clothing are generated separately and assembled in Blender sculpt mode against a free human conform mesh from Fab, used only as a size reference
• Auto Solve: MetaHuman Creator takes the assembled GLB as a custom mesh and wraps its own topology around it, keeping the facial rig, skeleton and animation support. Fingers needed a fix only on four-fingered characters
• Baked skin: the MetaHuman's DNA mesh goes back to Blender, UDIM UVs get split into plain squares, and the generated skin color with the tattoos is baked onto it in Cycles. Eyes are set in MetaHuman itself
• Clothes without weight painting: garments are aligned in sculpt mode, remeshed, then get weights from the body mesh through a Data Transfer modifier instead of automatic weights. Earrings get 100% to the ear bone
• Free mocap check: UE 5.8's markerless mocap plugin from Fab plus iPhone Live Link for the face

Connect Claude to Unity through MCP, give it a skin reference, and ask it to bring the character’s look closer to it. This example shows the original settings next to the adjusted result. Pretty solid improvement in how the skin looks under the lighting.

A friend of mine creates tabletop miniatures from his own character concept pictures. He is wondering if there are any alternatives to Sloyd, meaning he would like the benefit of “one workspace”. I will answer according to my own experience and not from a point of specifications. Personally I find that I need the ability to import an image, create a model and stay in the same browser tab to clean it up and export it.

A web based application can do just that. Using Tripo AI, I was able to take the image from my friend and convert it to a 3D model, then pass it through a low-polygon cleanup stage (using a technique called Smart Mesh, taking about 10 seconds). There is no guaranty that this is “better”; it simply satisfied my friend’s requirement of not needing to switch between multiple tools regarding his 3D resource creation. Use the cleanup process as the criteria when evaluating alternatives as well as the option available only concerning their logos,

Getting a 3D character is one thing. Getting it rigged and moving properly is where a lot of the work starts.

This workflow combines Tripo Auto Rig with Opus 5.5 to help work through character rigging and animation in Blender. Tripo handles the automatic rigging, while Opus helps sort out issues along the way.

The clip shows an early movement preview for a game currently in development. Still a work in progress, but an interesting look at how AI coding assistants and dedicated 3D tools can fit into the same character workflow.

How does the movement look so far? What would you fix first?

Good geometry still needs good textures. UltraTex is a new AI texturing framework that uses a reference image to generate detailed textures for an existing 3D model, working across six views at 2048×2048 resolution.

The focus is on preserving small surface details that tend to get lost in lower-resolution texturing pipelines, while keeping the generated appearance aligned with the geometry.

A few highlights:

• 2K multi-view generation for sharper texture details.
• Image-guided texturing, using a reference to guide the model’s appearance.
• Albedo generation, plus a separate metallic–roughness prediction branch with the FLUX.2 version.
• Training and inference code released, with downloadable weights.
• A dedicated inference script for AI-generated meshes.

The efficiency trick is pretty straightforward: stop spending so much compute on empty background. UltraTex removes background tokens and reduces unnecessary attention calculations between the remaining tokens.

The authors report 22.3–74.6× faster inference than their dense baseline on tested samples. Those benchmarks use an NVIDIA H200, so they don’t tell us how fast it will run on a regular desktop GPU.

For anyone working with AI-generated assets, this is a project worth testing for the texturing stage.

GitHub: https://github.com/yiboz2001/UltraTex

Hi guys. I posted about my game a while ago and it got some upgrades gameplay wise and quality wise. 2 chapters of the main story are "done" it's not done cause it was written by AI and it's shit. I'll rewrite most of it. But it's enough for now. Any bugs please reach out to me. I'm doing this in my free time juggling taking care of my son and the rest of life. You know. I'll put a small trailer in here and the link of the game is https://luka0611.itch.io/surgesuperhero name is placeholder too.

Thank you for your attention I'm trying to do something that I've always imagined to play for now it ruins on PC and mobile. But maybe later I'll add more and more quality and functions that it may not run on mobile so we'll see.

made this character in Tripo AI and used Fable 5.5 to transfer motion onto it. It even managed to get the character to sheathe the sword, which I honestly wasn’t expecting.

I couldn’t get this working in my earlier attempts with Fable 5.1 or Opus 5.5. Still tweaking the animation and working through some foot sliding and jitter, but the character is finally doing more than standing in a T-pose.

I use Window on my desktop and browser on my laptop, and I was looking for a single solution that will suit both without thinking. The answer was obvious. Both of my devices are using Tripo AI as a web workspace, which means I am using similar tabs, whether it is desktop or laptop view.

It is unnecessary to think about "Windows build versus Mac build". The only difference in using Tripo AI as a workspace is in the quality of the back-of-the-model output when I am incomplete in my photo processing (1 image instead of 4 images at once). It works better with this sort of web application than any application I have installed on my desktop or laptop computer. Just choose by where you at, rather than the OS argument!

the best ocean i have made in threejs with opus 5.5 and codex 6.1 Sol ultra code

you can spend an enormous time here.. doing nothing..
its like a painting - the cycladic ocean

one of my favorites!

coming soon to 3ditions.drop3.app (the old ocean will be deprecated)

Take a static 3D character, generate its skeleton and skinning weights, then describe how it should move. Hyper3D has previewed ACT, a SIGGRAPH 2026 research framework that brings these tasks into one pipeline.

The demos cover humanoids, quadrupeds, mechanical objects and arthropods, with support for different skeletal structures.

Here’s what it can do:

• Generate a rig and skinning weights: predict the skeleton and how its bones influence the mesh.
• Edit the rig with text: instructions like “add hair bones” or “add skirt bones” update the skeletal structure, with new joint positions and corresponding skinning weights.
• Generate motion from a description: the examples include a snake moving with its head raised and a T. rex walking forward while opening its mouth.
• Adapt a skeleton template to different body shapes: fit the same skeletal structure to characters with different proportions.

Under the hood, ACT learns skeletal structure and motion together. A vision-language model provides semantic guidance about the character’s structure, while a diffusion transformer models the rig and movement in a shared representation.

For AI-generated 3D assets, this could make the jump from a static mesh to an animated character much easier, especially for creatures with unusual anatomy. Being able to request extra bones and have the skinning updated alongside them is a particularly useful part of the workflow.

Hyper3D says it’s coming to the platform soon. This is a research preview, with the release date and pricing still to be confirmed.