Add link to paper and task category

README.md

@@ -1,5 +1,38 @@
 ---
 license: cc-by-nc-sa-4.0
+task_categories:
+- image-to-image
 ---
 
-GitHub Repository: https://github.com/caijie0620/OpenRR-5k for more details
+# OpenRR-5k
+
+The OpenRR-5k dataset is a large-scale benchmark for single-image reflection removal (SIRR) in the wild, introduced as part of the [NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods](https://huggingface.co/papers/2604.10321). 
+
+The dataset consists of real-world images covering a variety of reflection scenarios and intensities.
+
+GitHub Repository: [caijie0620/OpenRR-5k](https://github.com/caijie0620/OpenRR-5k)
+
+## Dataset Structure
+
+The dataset consists of the following components:
+- `train_5000.zip`: contains 5,000 paired input images and corresponding ground truth (GT) images.
+- `val_300_blended.zip`: contains 300 validation input images.
+- `val_300_transmission.zip`: contains 300 validation ground truth images.
+- `test_100_blended.zip`: contains 100 test input images (without ground truth).
+
+For more details regarding the challenge, please visit the [CodaBench Competition](https://www.codabench.org/competitions/12971/) page.
+
+## Citation
+
+If you find this dataset helpful in your research, please cite the following work:
+
+```bibtex
+@inproceedings{cai2025openrr,
+  title={Openrr-5k: A large-scale benchmark for reflection removal in the wild},
+  author={Cai, Jie and Yang, Kangning and Ouyang, Ling and Fu, Lan and Ding, Jiaming and Shen, Jinglin and Meng, Zibo},
+  booktitle={2025 IEEE 8th International Conference on Multimedia Information Processing and Retrieval (MIPR)},
+  pages={14--19},
+  year={2025},
+  organization={IEEE}
+}
+```