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Document all models + link dedicated repos for the trained ones (RMIB, MeshSeg)

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@@ -34,4 +34,45 @@ CC0-1.0), trained on CC0 content from ambientCG / Poly Haven. Converted with
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  QtMeshEditor downloads these on first use into `<AppData>/ai_models/pbr/`.
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- More info in [QtMesh Cloud website](https://qtmesh.dev)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  QtMeshEditor downloads these on first use into `<AppData>/ai_models/pbr/`.
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+ More info in [QtMesh Cloud website](https://qtmesh.dev)
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+ ## Texture upscaling
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+
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+ `RealESRGAN_x2plus.onnx`, `RealESRGAN_x4plus.onnx` — 2×/4× super-resolution.
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+ ONNX re-exports of **Real-ESRGAN** ([xinntao](https://github.com/xinntao/Real-ESRGAN),
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+ **BSD-3-Clause**). Downloaded into `<AppData>/ai_models/pbr/`. Credit: xinntao.
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+
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+ ## Auto-rig skeleton prediction (UniRig)
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+
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+ `unirig/encoder.onnx`, `unirig/decoder.onnx`, `unirig/embed.onnx` — ML skeleton
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+ prediction for unrigged meshes. These are **ONNX re-exports** of
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+ **[VAST-AI/UniRig](https://huggingface.co/VAST-AI/UniRig)** (SIGGRAPH 2025 — MIT
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+ code + MIT weights, trained on Articulation-XL2.0 / CC-BY-4.0). Converted with
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+ `scripts/export-unirig-onnx.py` in the QtMeshEditor repo. Downloaded into
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+ `<AppData>/ai_models/unirig/`. Credit for the weights: VAST-AI-Research.
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+
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+ ## Animation in-betweening (RMIB) — trained by us
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+
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+ `inbetween/rmib.onnx` — fills the gap between two keyframes with smooth
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+ intermediate motion. **Trained from scratch** by the QtMeshEditor project on the
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+ permissive [CMU Graphics Lab Motion Capture Database](http://mocap.cs.cmu.edu).
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+ Beats spherical-linear interpolation by >2× on held-out CMU motion.
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+ **Dedicated repo:** [fernandotonon/QtMeshEditor-rmib-inbetween](https://huggingface.co/fernandotonon/QtMeshEditor-rmib-inbetween).
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+ Downloaded into `<AppData>/ai_models/inbetween/`. License: CC-BY-4.0.
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+
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+ ## Mesh part segmentation — trained by us
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+
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+ `segment/meshseg.onnx` — predicts head / torso / arm / leg labels per point
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+ (PointNet++-style). **Trained from scratch** by the QtMeshEditor project on
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+ **synthetic, permissively-derived** data (per-vertex labels from rigged-humanoid
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+ bone weights — CC0). Sidesteps the non-commercial ShapeNet-Part / PartNet
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+ datasets. **Dedicated repo:** [fernandotonon/QtMeshEditor-mesh-segmentation](https://huggingface.co/fernandotonon/QtMeshEditor-mesh-segmentation).
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+ Downloaded into `<AppData>/ai_models/segment/`. License: CC-BY-4.0.
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+
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+ ---
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+
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+ These models power the AI-assisted authoring features in
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+ **[QtMeshEditor](https://github.com/fernandotonon/QtMeshEditor)** and its
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+ companion **QtMesh Cloud** ([qtmesh.dev](https://qtmesh.dev)). Each downloads on
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+ first use and runs locally (offline). Mixed licenses per model as noted above
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+ (CC0 / BSD-3 / MIT-derived / CC-BY-4.0); see each section + the QtMeshEditor
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+ `THIRD_PARTY_AI_MODELS.md`.