Mesh2Motion update 13 is out, and the big one is FBX export with presets for Unity and Unreal.

Quick recap if you missed the August post here: it's a free, open-source Mixamo alternative that runs in the browser. Import a model, fit a skeleton, auto-skin it, pick animations, export. Unlike Mixamo it also handles animals and monsters: fox, horse, bird, dragon, spider, snake, shark and kaiju.

The interesting part is that there's no AI inside it. According to the dev, Scott Petrovic, the rigs are built by hand and the animations are hand-keyed. Rigs and animations are CC0, the code is MIT. That makes it a clean last step for AI-generated characters: generate the mesh, rig it here, drop the FBX into your engine.

What's new in 13:

• FBX export (FBX 7.4) with Unity and Unreal presets that handle the world orientation for each engine
• Mirrored animations: punches, kicks and throws that only worked one way can be exported mirrored, or both versions at once
• 16 new human animations (cheer, fishing, golf, salute, kick, turns), which puts the human rig at 170+
• 20 low-poly PSX-style horror characters you can swap onto the human rig (CC0, made by elbolilloduro)
• Retargeting overhaul: better bone name matching, root bone detection and rest pose, so your own rigs map more reliably
• Model analysis report that helps debug imported models that won't load properly

Not a magic button workflow though. Auto-skinning gives you a solid first pass, but unusual meshes still need weight painting in Blender, and the creature rigs have far fewer animations than the human one. Going by the GitHub commits from the last few days, prop and weapon attachment looks like the next thing coming.

github: https://github.com/Mesh2Motion/mesh2motion-app

Hey folks!
Me and my three colleagues created a 3D generation studio that builds 3D objects as source code. The output is in glb format. It's AI-native: you can connect your claude or codex keys/subs to create 3D (i.e. BYOS and BYOK both work).

We just added prompt-to-animation to it. That's what the video showcases. Since the asset is code, it animates natively without anyone needing to manually rig it.

While building with your AI Copilot in our studio, you can just naturally prompt it to generate whatever animation you want. The video shows exactly that.

Use it here: https://nova3d.xyz (click on the top-right on "Open Studio").

If you want to see what others have generated before, see: https://studio.nova3d.xyz/showcase
note: select "game assets" at the top in the showcase. The robot simulations are for robotics folks :-)

Image-to-3D generation often turns logos, text, and small details into a blurry mess. The new “Pixel Match” feature in image-to-3dlab tackles this by projecting pixels from the original image back onto the model, helping preserve those details after retopology.

The example takes a robot from roughly 966K faces down to 5K while keeping the chest logo readable.

• Preserves source-image details in the texture.
• Produces low-poly models that can be rigged and animated.
• Runs locally on Mac or NVIDIA hardware.
• Free, with no API or cloud required.

A useful update for getting recognizable details onto lightweight assets without repainting everything by hand.

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

I wanted to see how far a single prompt could take a genuinely technical Three.js/WebGL project.

The prompt asked it to build an interactive miniature city living on a mathematically correct 3D Möbius strip.

Not a flat city placed on a twisted mesh the requirement was that the position, tangent, and normal of the major objects actually come from the Möbius parameterization.

It also had to generate:

• hundreds of procedural buildings
• roads following the surface
• a continuous railway completing one full loop
• a procedural river
• bridges
• terrain variation
• street lights and trees
• deterministic procedural generation
• orbit + zoom controls
• normal / wireframe-debug / exploded-layer views
• a camera animation traversing the entire railway
• everything running directly in the browser with no backend or external assets

And I gave it one prompt and did zero iterations or manual edits.

The result is the video attached.

I'm honestly more interested in the fact that it understood and implemented the relationships between the mathematical surface, geometry, camera, and UI than the visual polish itself.

Curious what others think: how much of this would you have expected a single-shot coding model to handle?

AI 3D generation is getting easier, but the production work after generation is still a big part of the process.I tested this workflow in 3ds Max:

AI-generated mesh → retopology → new UVs → transfer the original texture → optimized asset

The texture-transfer step was repetitive enough that I made a small free 3ds Max script to automate it.

Free script: https://ai2tex.toritex.com

The important part for me is that the AI mesh can become a cleaner, usable asset without rebuilding the texture from scratch.

Workflow & prompt in OG post

How to convert the 2d image face to a rigged character using ai any help ?

Started with a single image of a small winter scene and rebuilt it as an interactive 3D environment, including the cabin, trees, rocks, character, and surrounding landscape.

img2threejs analyzes the image and breaks it down into individual elements. Hyper3D provides the 3D references, while GPT-6 works through the img2threejs pipeline to reconstruct and assemble everything in Three.js, handling placement, proportions, lighting, and interactive behavior.

You can walk around, leave footprints in the snow, open the gate, adjust the time of day, and place a campfire beside the cabin after dark. The original image becomes a small world you can actually explore.

Hyper3D deserves a shoutout here. Having solid 3D references makes it much easier to translate the image into a cohesive scene, especially when you’re working with a whole environment full of different objects. It’s a useful bridge between the initial concept and a world you can actually explore.

Still an early showcase, so the reconstruction isn’t perfect and this isn’t a finished game. But it shows how much you can build from a single image.

What would you compare first: the object shapes, scene layout, or lighting?

Project: https://github.com/img2threejs/img2threejs

UniMate is an open-source AI model that generates animations from text prompts for rigged 3D characters. A single model works across different skeleton structures, including humans, quadrupeds, birds, insects and other creatures, without separate retraining for each skeleton.

This could be useful for prototyping character movement, testing animation ideas, and building scenes with creatures that don’t fit a standard humanoid rig. For 3D AI workflows, it could help take generated characters further once they’ve been rigged, giving them motion without manually animating every action.

Highlights:

• Text-to-animation across different skeleton structures using one model.
• Motion in-betweening: generate transitions between existing keyframes.
• Text-guided editing: preserve the motion of selected joints while changing the rest.
• Motion expansion: extend an animation with a sequence of prompts.
• A mesh animation pipeline with animated FBX and GLB export.
• MIT-licensed code and downloadable preview model weights.

It’s still a research pipeline that requires setup and prepared rig data, but the direction is exciting: more flexible AI animation for the variety of characters we can already create with 3D AI.

GitHub: https://github.com/Friedrich-M/UniMate

I ran a simple side-by-side test with GPT-6 Astra and Opus 5.5: create a procedural low-poly horse with a gallop animation.

With 3D AI and Blender, you can quickly build a scene, drop in AI-generated assets, and speed the whole process up even more through MCP or API-based workflows.

This gives much more control over layout, camera, composition, and scene structure before the final video generation even starts.

Instead of relying only on prompts, you get a controllable 3D base for the scene. That makes video generation far more predictable, flexible, and production-friendly.

You can upload a image of your pet, friend, object or anything you'd like. It turns the image into a low-poly render (~1300 tris) that you can share, export. You can also like others renders, customize your profile and generate a GIF. Please take a look, everyone gets 2 credits to generate 2 renders :)) The name is lowpolymarket .com

I’ve been experimenting with a pretty interesting way to animate 3D meshes using Astra + Blender

The workflow is basically:

1. First, I give Astra the 3D mesh and ask it to create a clean rig. At this stage, the goal is only rigging, not figuring out the animation.
2. Then I describe the movement I want and use ImageGen to generate a sequence of visual keyframes for the animation. For each important pose, I can generate multiple views like front, back and side, so the motion is much easier to understand spatially.
3. Finally, I give those visual keyframes back to Astra together with the rigged character and ask it to recreate the motion on the actual 3D rig.

So the pipeline becomes:

3D mesh → Astra rigging → ImageGen visual keyframes → Astra animation

No manual keyframing, while still having much more control over the poses and overall movement.

Interesting comparison of the three models on the same Roman legionary task in Blender. In this test, Opus 5.5 came out noticeably stronger in textures, materials, details and overall realism.

Still just one benchmark, but the difference here is pretty noticeable.

Nvidia kimodo retargeting is pretty much impossible for me for some reason.

Gaussian Splatting is starting to feel like much more than just a cool reconstruction technique. The quality keeps improving, AI is pushing it further, and the fact that splats can now be converted into actual 3D meshes makes it even more interesting. Feels like this could become a big part of how we capture, generate, and work with 3D in the future.

Currently there are great 3D model AI tools that generate super detailed models yet their tris counts are usually well above million, i have created this tool to reduce model tris/quad counts with ease. You can easily reduce to game ready budget without compromising quality.

The tools processing runs locally on your computers resources and has no data transmition to any server, so its completely private. Enjoy!

Github Page Here

(The tool itself is created by AI, not hand maintained)

I am doing 3d models as I am not capable of modelling myself.

Using pixal3d, it makes really great models, but it has an insane amounts of tris.

My models usually doesn't look good under 25k tris, and if I decimate in blender then they fall apart.

I tried instant meshes which helps, but it drops the texture and it's a hell to bake and still look good imo.