|
Download README.md from ngoctham/MoCapAnythingV2-weights: direct link, hf CLI and curl.
- Browser
- Download file 2.58 kB
-
https://huggingface.co/ngoctham/MoCapAnythingV2-weights/resolve/main/README.md
- Command line
-
hf download hf://ngoctham/MoCapAnythingV2-weights/README.md
-
curl -L -o README.md https://huggingface.co/ngoctham/MoCapAnythingV2-weights/resolve/main/README.md
2.58 kB
| license: mit | |
| pipeline_tag: keypoint-detection | |
| tags: | |
| - arxiv:2604.28130 | |
| - motion-capture | |
| - keypoint-detection | |
| - animation | |
| - pose-estimation | |
| - bvh | |
| - retargeting | |
| - animals | |
| library_name: pytorch | |
| # MoCapAnything V2 — Pretrained Weights | |
| **End-to-End Motion Capture for Arbitrary Skeletons.** | |
| This repo hosts the released end-to-end `video2pose2rot` checkpoint: a single network that maps a monocular video (plus a one-frame reference pose of the target species) directly to BVH-ready joint rotations — no analytical IK in the loop. | |
| - 📄 Paper: [MoCapAnything V2 on HF Papers](https://huggingface.co/papers/2604.28130) · [arXiv:2604.28130](https://arxiv.org/abs/2604.28130) · Project page: [animotionlab.github.io/MoCapAnythingV2](https://animotionlab.github.io/MoCapAnythingV2/) | |
| - 💻 Code: [github.com/phongdaot/MocapAnything](https://github.com/phongdaot/MocapAnything) | |
| - 🗂 Demo data: [kehong/MoCapAnythingV2-data-sample](https://huggingface.co/datasets/kehong/MoCapAnythingV2-data-sample) | |
| ## Files | |
| | File | Description | | |
| | --- | --- | | |
| | `video2pos2rot_epoch60.pt` | End-to-end video → pose → rotation model (≈464 MB) | | |
| The background remover (`briaai/RMBG-1.4`) and the video encoder (`facebook/dinov2-large`) are pulled automatically from their own HuggingFace repos at runtime — they are not re-hosted here. | |
| ## Usage | |
| ```bash | |
| git clone https://github.com/phongdaot/MocapAnything.git && cd MocapAnything | |
| pip install torch torchvision numpy opencv-python pillow matplotlib scipy scikit-image \ | |
| trimesh roma pyyaml tqdm huggingface_hub transformers gradio imageio-ffmpeg | |
| hf download kehong/MoCapAnythingV2-weights --local-dir ./checkpoints | |
| hf download kehong/MoCapAnythingV2-data-sample --repo-type dataset --local-dir ./demo/data | |
| # command-line inference on the bundled examples | |
| python inference/video2pose2rot.py --config demo/configs/demo_wild.yaml | |
| # or the interactive Gradio demo | |
| python demo/app.py | |
| ``` | |
| See the repo's [RUN.md](https://github.com/phongdaot/MocapAnything/blob/main/RUN.md) for the Blender render setup and full options. | |
| ## Citation | |
| ```bibtex | |
| @article{gong2026mocapanythingv2, | |
| title = {MoCapAnything V2: End-to-End Motion Capture for Arbitrary Skeletons}, | |
| author = {Gong, Kehong and Wen, Zhengyu and Phong, Dao Thien and | |
| Xu, Mingxi and He, Weixia and Wang, Qi and Zhang, Ning and | |
| Li, Zhengyu and Hou, Guanli and Lian, Dongze and He, Xiaoyu and | |
| Zhang, Mingyuan and Zhang, Hanwang}, | |
| journal = {arXiv preprint arXiv:2604.28130}, | |
| year = {2026} | |
| } | |
| ``` | |