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README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+  - image-segmentation
+tags:
+  - glass-surface-detection
+  - rgb-d
+  - scene-understanding
+  - pytorch
+pretty_name: RGBD-GSD-Net (RGB-D Glass Surface Detection Network)
+---
+
+# RGBD-GSD-Net — RGB-D Glass Surface Detection Network
+
+Pre-trained weights for the model introduced in:
+
+> **Leveraging RGB-D Data with Cross-Modal Context Mining for Glass Surface Detection**  
+> Jiaying Lin\*, Yuen-Hei Yeung\*, Shuquan Ye, Rynson W. H. Lau  
+> AAAI 2025  
+> [arXiv](https://arxiv.org/abs/2206.11250) · [Project Page](https://jiaying.link/aaai2025-rgbdglass/) · [Dataset (RGBD-GSD)](https://huggingface.co/datasets/garrying/RGBD-GSD)
+
+## Model Summary
+
+RGBD-GSD-Net detects glass surfaces by jointly processing RGB images and depth maps. It introduces two novel modules:
+
+- **Cross-Modal Context Mining (CCM)**: adaptively learns individual and mutual context features from RGB and depth information.
+- **Depth-Missing Aware Attention (DAA)**: explicitly exploits spatial locations where depth is missing (a strong indicator of glass surfaces) to guide detection.
+
+The backbone is a ResNeXt encoder shared across both modalities.
+
+| File | Description |
+|------|-------------|
+| `best.pth` | Best checkpoint (204 MB), saved as `{'model': state_dict, ...}` |
+| `results/our_best_results.zip` | Model predictions on the RGBD-GSD test set |
+
+## Loading the Weights
+
+```python
+import torch
+from networks.your_network import RGBDGlassNet   # from the code release
+
+model = RGBDGlassNet()
+checkpoint = torch.load("best.pth", map_location="cpu")
+model.load_state_dict(checkpoint["model"])
+model.eval()
+```
+
+Download the checkpoint:
+```bash
+huggingface-cli download garrying/RGBD-GSD-Net best.pth --local-dir ./weights
+```
+
+## Training Dataset
+
+This model was trained and evaluated on **RGBD-GSD**, the first large-scale RGB-D glass surface detection dataset:
+- 3,009 RGB-D images with binary glass surface masks and depth maps
+- Available at [garrying/RGBD-GSD](https://huggingface.co/datasets/garrying/RGBD-GSD)
+
+## Citation
+
+```bibtex
+@article{aaai2025_rgbdglass,
+  author    = {Lin, Jiaying and Yeung, Yuen-Hei and Ye, Shuquan and Lau, Rynson W.H.},
+  title     = {Leveraging RGB-D Data with Cross-Modal Context Mining for Glass Surface Detection},
+  journal   = {AAAI},
+  year      = {2025},
+}
+```
+
+## License
+
+Non-commercial use only — [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/).