r/TopologyAI

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

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.

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.

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

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?

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.

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)

Hey everyone! A few days ago, I had the idea of combining elements from some of my favorite games, and that’s how I came up with Parrygod. It’s a Hades-style roguelike with a parry mechanic like Sekiro’s, set in a Japanese cyberpunk world.

I started working on it about three days ago. My current workflow is to use Unity as the engine, generate characters and environments with Magnific, turn them into 3D models with Tripo, and animate them with Mixamo.

I also installed Unimate to try generating animations with AI, but I’m really struggling with rigging and getting good animations that actually fit the game. The character models themselves aren’t looking that great yet either.

Does anyone have any tips for improving the models, rigging, and animations? Or suggestions for a different workflow that could help me get better results?

My background is in design, and I don’t have any coding experience, so any help would be appreciated!

I'm using Opus 5.5 on max effort.

This is a pretty big step for local 3D AI generation.

A community-optimized build of Trellis.2 now runs on 8GB GPUs, while still keeping high-detail 3D output. According to the author, an RTX 3060 can complete a generation in around 13 minutes, and there is now a single-click installer similar to the A1111-style setup.

Links from the author:

Trellis.2 optimized release:
https://github.com/IgorAherne/TRELLIS.2-stableprojectorz/releases/tag/latest

Original bug discussion:
https://www.reddit.com/r/StableDiffusion/comments/1ssx9wg/i_optimized_trellis2_to_fit_inside_8gb_gpus_even/

StableProjectorz:
https://stableprojectorz.com/

Support / donate:
https://stableprojectorz.com/thanks/

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,

Hyper3D new Agentic Mode, powered by GPT-6.1 Sol, lets you “talk” to your 3D assets and keep refining them after generation.

• Parametric controls: adjust dimensions and proportions, from a building’s roof height to a forklift’s fork length.
• Custom sliders: ask for additional controls in plain language, then use them to fine-tune the model.
• Animation through prompts: describe a movement or gesture, like asking a mechanical hand to hold up three fingers.
• Targeted material edits: request a different material for a specific part, such as walnut wood for the upper kitchen cabinets.
• Multiple references: use images or a design sheet to guide generation, then continue refining the result through text.
• Editable geometry: Hyper3D demonstrates N-gon models aimed at further editing, including buildings and mechanical assets.

Still in beta, but the demos show a useful workflow: generate an asset, ask for changes, adjust its controls, and add movement.