Improve model card: Add pipeline tag, links, and usage

This PR enhances the model card by:
- Adding the `pipeline_tag: video-to-3d` to improve discoverability.
- Linking to the official paper: [Trace Anything: Representing Any Video in 4D via Trajectory Fields](https://huggingface.co/papers/2510.13802).
- Linking to the project page: [https://trace-anything.github.io/](https://trace-anything.github.io/).
- Linking to the GitHub repository: [https://github.com/ByteDance-Seed/TraceAnything](https://github.com/ByteDance-Seed/TraceAnything).
- Including a quick usage example directly from the GitHub repository.

README.md

@@ -1,3 +1,56 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+pipeline_tag: video-to-3d
+---
+
+# Trace Anything: Representing Any Video in 4D via Trajectory Fields
+
+This repository contains the official implementation of the paper [Trace Anything: Representing Any Video in 4D via Trajectory Fields](https://huggingface.co/papers/2510.13802).
+
+Trace Anything proposes a novel approach to represent any video as a Trajectory Field, a dense mapping that assigns a continuous 3D trajectory function of time to each pixel in every frame. The model predicts the entire trajectory field in a single feed-forward pass, enabling applications like goal-conditioned manipulation, motion forecasting, and spatio-temporal fusion.
+
+Project Page: [https://trace-anything.github.io/](https://trace-anything.github.io/)
+Code: [https://github.com/ByteDance-Seed/TraceAnything](https://github.com/ByteDance-Seed/TraceAnything)
+
+## Overview
+<div align="center">
+  <img src="https://huggingface.co/depth-anything/trace-anything/resolve/main/assets/teaser.png" width="100%"/>
+</div>
+
+## Installation
+For detailed installation instructions, please refer to the [GitHub repository](https://github.com/ByteDance-Seed/TraceAnything#setup).
+
+## Sample Usage
+To run inference with the Trace Anything model, first, download the pretrained weights (see GitHub for details). Then, you can use the provided script as follows:
+
+```bash
+# Download the model weights to checkpoints/trace_anything.pt
+# Place your input video/image sequence in examples/input/<scene_name>/
+
+python scripts/infer.py \
+  --input_dir examples/input \
+  --output_dir examples/output \
+  --ckpt checkpoints/trace_anything.pt
+```
+Results, including 3D control points and confidence maps, will be saved to `<output_dir>/<scene>/output.pt`.
+
+## Interactive Visualization
+An interactive 3D viewer is available to explore the generated trajectory fields. Run it using:
+```bash
+python scripts/view.py --output examples/output/<scene>/output.pt
+```
+For more options and remote usage, check the [GitHub repository](https://github.com/ByteDance-Seed/TraceAnything#interactive-visualization-%EF%B8%8F).
+
+## Citation
+If you find this work useful, please consider citing the paper:
+```bibtex
+@misc{liu2025traceanythingrepresentingvideo,
+      title={Trace Anything: Representing Any Video in 4D via Trajectory Fields}, 
+      author={Xinhang Liu and Yuxi Xiao and Donny Y. Chen and Jiashi Feng and Yu-Wing Tai and Chi-Keung Tang and Bingyi Kang},
+      year={2025},
+      eprint={2510.13802},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2510.13802}, 
+}
+```