Add model card for Track4World
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by
nielsr HF Staff - opened
README.md
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---
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license: other
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pipeline_tag: other
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tags:
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- 3d-tracking
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- video-understanding
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- 4d-reconstruction
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- computer-vision
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---
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# Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels
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Track4World is a feedforward model for efficient holistic 3D tracking of every pixel in a world-centric coordinate system from a monocular video. Built on a global 3D scene representation, Track4World applies a novel 3D correlation scheme to simultaneously estimate the pixel-wise 2D and 3D dense flow between arbitrary frame pairs.
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* **Paper:** [Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels](https://huggingface.co/papers/2603.02573)
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* **Project Page:** [jiah-cloud.github.io/Track4World](https://jiah-cloud.github.io/Track4World.github.io/)
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* **Repository:** [GitHub Repository](https://github.com/TencentARC/Track4World)
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---
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### 🖼️ Framework
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Track4World estimates dense 3D scene flow of every pixel between arbitrary frame pairs from a monocular video in a global feedforward manner, enabling efficient and dense 3D tracking of every pixel in the world-centric coordinate system.
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---
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## ⚙️ Setup and Installation
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```bash
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# Clone the repository with submodules
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git clone --recursive https://github.com/TencentARC/Track4World.git
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cd Track4World
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# Create and activate environment
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conda create -n track4world python=3.11
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conda activate track4world
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# Install PyTorch
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pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu121
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# Install dependencies
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pip install -r requirements.txt
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```
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Please refer to the [official GitHub README](https://github.com/TencentARC/Track4World) for detailed instructions on installing third-party modules and downloading weights.
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---
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## 🚀 Sample Usage
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You can perform tracking and reconstruction on the provided demo video using the following commands:
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### First Frame 3D Tracking (`3d_ff`)
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```bash
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python demo.py \
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--mp4_path demo_data/cat.mp4 \
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--mode 3d_ff \
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--Ts -1 \
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--save_base_dir results/cat
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```
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### Dense Tracking: Every Pixel, Every Frame (`3d_efep`)
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```bash
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python demo.py \
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--mp4_path demo_data/cat.mp4 \
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--coordinate world_depthanythingv3 \
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--mode 3d_efep \
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--Ts -1 \
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--ckpt_init checkpoints/track4world_da3.pth \
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--save_base_dir results/cat
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```
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---
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## Citation
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If you find Track4World useful for your research, please cite:
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```bibtex
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@article{lu2026track4world,
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title = {Track4World: Feedforward World-Centric Dense 3D Tracking of All Pixels},
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author = {Jiahao Lu and Jiayi Xu and Wenbo Hu and Ruijie Zhu and Chengfeng Zhao and Sai-Kit Yeung and Ying Shan and Yuan Liu},
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journal = {arXiv preprint arXiv:2603.02573},
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year = {2026}
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}
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```
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