Add model card, pipeline tag, and links to paper and code

README.md

@@ -1,3 +1,66 @@
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 license: cc-by-nc-sa-4.0
+pipeline_tag: image-segmentation
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+
+# SAM2Matting: Generalized Image and Video Matting
+
+This repository contains the official checkpoints for **SAM2Matting**, a generalized matting framework that decouples high-level tracking from dedicated low-level matting to support robust image and video matting of any open-world targets.
+
+[📄 Paper](https://huggingface.co/papers/2606.27339) | [🏠 Project Page](https://henghuiding.com/SAM2Matting/) | [💻 GitHub](https://github.com/FudanCVL/SAM2Matting)
+
+<p align="center">
+  <img src="https://raw.githubusercontent.com/FudanCVL/SAM2Matting/main/assets/teaser.png" width="90%" alt="SAM2Matting qualitative results"/>
+</p>
+
+## Highlights
+- **Decoupled design**: Combines a VOS tracker for temporal consistency with ROI Detection & Progressive Matting for fine details.
+- **Image-only training, video SOTA**: Strong zero-shot video matting performance without requiring expensive video matting datasets.
+- **Diverse prompts**: Supports masks, points, boxes, and text prompts.
+- **Open-world generalization**: Robust matting for humans, animals, anime, translucent objects, and rapid-motion scenes.
+
+## Installation
+
+To run SAM2Matting locally, clone the repository and install the dependencies:
+
+```bash
+# clone the repo and enter directory
+git clone https://github.com/FudanCVL/SAM2Matting.git
+cd SAM2Matting
+
+# create and activate conda environment
+conda create -n sam2matting python=3.10 -y
+conda activate sam2matting
+
+# install required packages
+pip install -r requirements.txt
+```
+
+## Quick Start
+
+The codebase provides separate inference scripts for image and video matting. 
+
+To run video matting on a sample with SAM2-based trackers, run:
+
+```bash
+python inference_video_sam2.py --save_mp4
+```
+
+To enable compilation for faster execution (though the first run may be slower):
+
+```bash
+python inference_video_sam2.py --save_mp4 --compiled
+```
+
+## Citation
+
+If you find SAM2Matting useful in your research, please consider citing the work:
+
+```bibtex
+@inproceedings{SAM2Matting,
+  title={{SAM2Matting}: Generalized Image and Video Matting},
+  author={Shen, Ruiqi and Jie, Guangquan and Liu, Chang and Ding, Henghui},
+  booktitle={European Conference on Computer Vision (ECCV)},
+  year={2026}
+}
+```