Add model card, project links, and pipeline tag

README.md

@@ -1,3 +1,62 @@
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 license: cc-by-nc-sa-4.0
+pipeline_tag: image-segmentation
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+
+# SAM-MT: Real-Time Interactive Multi-Target Video Segmentation
+
+This repository contains the official checkpoint for **SAM-MT**, presented in the paper [SAM-MT: Real-Time Interactive Multi-Target Video Segmentation](https://huggingface.co/papers/2607.08688).
+
+* **Project Page:** [henghuiding.com/SAM-MT](https://henghuiding.com/SAM-MT/)
+* **Repository:** [GitHub - FudanCVL/SAM-MT](https://github.com/FudanCVL/SAM-MT)
+
+**SAM-MT** is an efficient interactive multi-target video segmentation framework that maintains near-single-object efficiency (FPS and VRAM) as target count increases, while maintaining robust video segmentation performance.
+
+<p align="center">
+  <img src="https://raw.githubusercontent.com/FudanCVL/SAM-MT/main/assets/teaser.png" width="100%">
+</p>
+
+## Highlights
+* **Real-time speed**: 36+ FPS with 10 targets on a single NVIDIA RTX A6000 GPU.
+* **Individual-global representation**: Models individual targets and global scene within a unified framework.
+* **Interactive multi-target video segmentation**: Simple clicks for target specification.
+
+## Quick Start
+
+### Installation
+```bash
+# clone the repo and enter directory
+git clone https://github.com/FudanCVL/SAM-MT.git
+cd SAM-MT
+
+# create and activate conda environment
+conda create -n sammt python=3.10 -y
+conda activate sammt
+
+# install required packages
+pip install -r requirements.txt
+```
+
+### Inference
+By default, place the downloaded checkpoint under the `checkpoints/` directory.
+
+```bash
+# Basic inference (coordinates required)
+python inference.py
+
+# Interactive Gradio demo
+python inference_gradio.py
+```
+
+## Citation
+
+If you find SAM-MT useful in your research, please consider citing:
+
+```bibtex
+@inproceedings{SAM-MT,
+  title={{SAM-MT}: Real-Time Interactive Multi-Target Video Segmentation},
+  author={Shen, Ruiqi and Liu, Chang and Ding, Henghui},
+  booktitle={European Conference on Computer Vision (ECCV)},
+  year={2026}
+}
+```