Update README

README.md

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-license: openrail
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+# UnderWaterNet Dataset
+
+Official repository for the UnderWaterNet dataset, a comprehensive collection of underwater and surface images for computer vision tasks including 2D object detection and 6D pose estimation.
+
+## Paper
+
+**[Model-Based Underwater 6D Pose Estimation From RGB](https://ieeexplore.ieee.org/abstract/document/10265120)**  
+Published in IEEE Xplore
+
+## Official Website
+
+[https://sapienzadavide.github.io/uwpose.github.io/index.html](https://sapienzadavide.github.io/uwpose.github.io/index.html)
+
+## Dataset Structure
+
+### Real Underwater & Surface Images (UWds)
+
+Compressed archives of real-world images across different environmental conditions:
+
+- `UW6d/asphalt.tar.gz` (4.6GB) - Asphalt surface images
+- `UW6d/drydirt.tar.gz` (3.4GB) - Dry dirt surface images  
+- `UW6d/dryshadow.tar.gz` (2.5GB) - Shadowed dry surface images
+- `UW6d/drywhite.tar.gz` (3.8GB) - White dry surface images
+- `UW6d/grass.tar.gz` (4.5GB) - Grass surface images
+- `UW6d/uwLED.tar.gz` (530MB) - Underwater LED-lit images
+- `UW6d/uwshadow.tar.gz` (1.9GB) - Underwater shadowed images
+- `UW6d/w_p_occluded.tar.gz` (956MB) - Water with partial occlusion
+
+### 3D Object Models (UW6d)
+
+- `UW6d/objects_ply/` - PLY mesh files for 6D pose estimation tasks
+
+### 2D Object Detection Dataset (UW2d)
+
+Real-world images for 2D object detection:
+
+- `UW2d/cube.tar.gz` - Cube object images
+- `UW2d/cup.tar.gz` - Cup object images
+- `UW2d/hotstab.tar.gz` - Hotstab object images
+- `UW2d/jar.tar.gz` - Jar object images
+- `UW2d/multiple_objects.tar.gz` - Multi-object scenes
+
+### Synthetic Datasets
+
+Unity-generated synthetic data for training:
+
+- `synthetic_2d.tar.gz` - Synthetic dataset for 2D object detection (no background)
+- `synthetic_6d.tar.gz` - Synthetic dataset for 6D pose estimation (sandy background)
+
+## Tasks Supported
+
+- 6D pose estimation
+- 2D object detection
+
+## Citation
+
+If you use this dataset in your research, please cite:
+```bibtex
+@ARTICLE{10265120,
+  author={Sapienza, Davide and Govi, Elena and Aldhaheri, Sara and Bertogna, Marko and Roura, Eloy and Pairet, Èric and Verucchi, Micaela and Ardón, Paola},
+  journal={IEEE Robotics and Automation Letters}, 
+  title={Model-Based Underwater 6D Pose Estimation From RGB}, 
+  year={2023},
+  volume={8},
+  number={11},
+  pages={7535-7542},
+  keywords={Pose estimation;Three-dimensional displays;Sensors;Solid modeling;Task analysis;Cameras;Robot sensing systems;Computer vision for manipulation;dataset;manipulation;pose estimation;underwater},
+  doi={10.1109/LRA.2023.3320028}
+  }
+
+```
+
+## License
+
+openrail