Improve model card: add paper link, authors, and project info

README.md

@@ -1,28 +1,67 @@
 ---
-license: apache-2.0
-language:
-- en
 base_model:
 - syscv-community/sam-hq-vit-large
+language:
+- en
+license: apache-2.0
 pipeline_tag: image-segmentation
+tags:
+- feature-matching
+- computer-vision
+- co-visibility
 ---
 
-# SAMatcher
+# SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching
 
-SAMatcher is a robust feature matching method that models cross-view co-visibility with Segment Anything (SAM), improving correspondence under viewpoint/illumination/texture changes.
+SAMatcher is a feature matching framework that formulates correspondence estimation through co-visibility modeling. Built upon the Segment Anything Model (SAM), it introduces a symmetric cross-view interaction mechanism that enables bidirectional feature exchange and cross-view semantic alignment to improve correspondence under large viewpoint, illumination, and scale variations.
 
-- GitHub: https://github.com/TwSphinx54/SAMatcher
-- Project Page: https://xupan.top/Projects/samatcher
+- **Paper:** [SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching](https://huggingface.co/papers/2606.03406)
+- **Authors:** Xu Pan, Qiyuan Ma, Jintao Zhang, He Chen, Xianwei Zheng
+- **GitHub:** [https://github.com/TwSphinx54/SAMatcher](https://github.com/TwSphinx54/SAMatcher)
+- **Project Page:** [https://xupan.top/Projects/samatcher](https://xupan.top/Projects/samatcher)
 
 ## Quick Start
 
+### Installation
+
+The project uses `uv` for dependency management. Recommended Python version is 3.12.
+
+```bash
+# Clone the repository
+git clone https://github.com/TwSphinx54/SAMatcher.git
+cd SAMatcher
+
+# Install dependencies using uv
+uv sync --frozen
+```
+
+### Download Weights
+
+You can download the model weights using the Hugging Face CLI:
+
 ```bash
-huggingface-cli download SSSSSphinx/SAMatcher --local-dir ./SAMatcher
+huggingface-cli download SSSSphinx/SAMatcher --local-dir ./weights/SAMatcher
 ```
 
 Then follow the official training/evaluation scripts in the GitHub repository.
 
-## Notes
+## Evaluation
+
+To evaluate on MegaDepth, use the provided script:
+
+```bash
+bash scripts/evaluate_megadepth.sh
+```
+
+## Citation
+
+If you find SAMatcher useful in your research, please consider citing:
 
-- Recommended Python: 3.12 (if using lockfile setup)
-- Main dependencies include PyTorch + CUDA 12.1 and flash-attn
+```bibtex
+@article{pan2024samatcher,
+  title={SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching},
+  author={Pan, Xu and Ma, Qiyuan and Zhang, Jintao and Chen, He and Zheng, Xianwei},
+  journal={arXiv preprint arXiv:2606.03406},
+  year={2024}
+}
+```