Improve model card

README.md

@@ -1,7 +1,7 @@
 ---
-license: mit
 language:
 - en
+license: mit
 metrics:
 - recall
 - precision
@@ -14,4 +14,45 @@ tags:
 - mesh-reconstruction
 - pose-aware
 - icme-2026
----
+---
+
+# GraphiContact: Pose-aware Human-Scene Robust Contact Perception for Interactive Systems
+
+This repository contains the pre-trained checkpoints for **GraphiContact**, a novel framework for monocular vertex-level human-scene contact prediction and 3D human mesh reconstruction.
+
+[**Paper (arXiv)**](https://huggingface.co/papers/2603.20310) | [**Official GitHub Repository**](https://github.com/Aveiro-Lin/GraphiContact)
+
+## Overview
+
+GraphiContact jointly addresses vertex-level contact prediction and single-image 3D human mesh reconstruction. It uses reconstructed body geometry as a scaffold for contact reasoning, integrating pose-aware features with human-scene interaction understanding.
+
+### Key Features
+
+*   **Pose-aware Framework**: Transfers complementary human priors from pretrained Transformer encoders to predict per-vertex human-scene contact on the reconstructed mesh.
+*   **SIMU Training Strategy**: Introduces a Single-Image Multi-Infer Uncertainty (SIMU) training strategy with token-level adaptive routing. This simulates occlusion and noisy observations during training while preserving efficient single-branch inference at test time.
+*   **Robust Perception**: Specifically designed to handle real-world scenarios with perceptual noise and occlusions, making it suitable for interactive systems like embodied AI and rehabilitation analysis.
+
+<p align="center">
+  <img src="https://github.com/Aveiro-Lin/GraphiContact/raw/main/docs/Overview.png" width="850">
+</p>
+
+## Installation and Usage
+
+For detailed instructions on environment setup, downloading model weights, and running inference demos, please refer to the [official GitHub repository](https://github.com/Aveiro-Lin/GraphiContact).
+
+## Citation
+
+If you find this work useful for your research, please consider citing the paper:
+
+```bibtex
+@inproceedings{lin2026graphicontact,
+  title={GraphiContact: Pose-aware Human-Scene Robust Contact Perception for Interactive Systems},
+  author={Lin, Aveiro and others},
+  booktitle={IEEE International Conference on Multimedia and Expo (ICME)},
+  year={2026}
+}
+```
+
+## License
+
+The research code is released under the **MIT license**. Note that the model has dependencies on the SMPL and MANO models, which are subject to their own [Software Copyright License](https://smpl.is.tue.mpg.de/modellicense) for non-commercial scientific research purposes.