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--- |
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license: cc-by-sa-4.0 |
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task_categories: |
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- image-to-image |
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language: |
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- en |
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tags: |
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- rain |
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pretty_name: ' High-resolution Rainy Image' |
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size_categories: |
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- 1K<n<10K |
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--- |
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# High-resolution Rainy Image Synthesis: Learning from Rendering |
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This is the dataset in the paper "High-resolution Rainy Image Synthesis: Learning from Rendering" |
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* Project Page: https://kb824999404.github.io/HRIG/ |
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* Paper: https://arxiv.org/abs/2502.16421 |
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* Code: https://github.com/kb824999404/HRIG |
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<table> |
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<tr> |
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<td style="padding: 0;width=30%;"><img src="Imgs/lane/lane (1).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/lane/lane (2).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/lane/lane (3).jpg" /></td> |
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</tr> |
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<tr> |
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<td style="padding: 0;width=30%;"><img src="Imgs/lane/lane (4).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/lane/lane (5).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/lane/lane (6).jpg" /></td> |
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</tr> |
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<tr> |
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<td style="padding: 0;width=30%;"><img src="Imgs/citystreet/citystreet (1).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/citystreet/citystreet (2).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/citystreet/citystreet (3).jpg" /></td> |
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</tr> |
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<tr> |
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<td style="padding: 0;width=30%;"><img src="Imgs/citystreet/citystreet (4).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/citystreet/citystreet (5).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/citystreet/citystreet (6).jpg" /></td> |
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</tr> |
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<tr> |
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<td style="padding: 0;width=30%;"><img src="Imgs/japanesestreet/japanese (1).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/japanesestreet/japanese (2).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/japanesestreet/japanese (3).jpg" /></td> |
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</tr> |
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<tr> |
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<td style="padding: 0;width=30%;"><img src="Imgs/japanesestreet/japanese (4).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/japanesestreet/japanese (5).jpg" /></td> |
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<td style="padding: 0;width=30%;"><img src="Imgs/japanesestreet/japanese (6).jpg" /></td> |
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</tr> |
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</table> |
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## HRI Dataset |
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The High-resolution Rainy Image (HRI) dataset in the rendering stage. |
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|
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<table style="text-align: center;"> |
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<tr> |
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<th>scene</th> |
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<th>dataset type</th> |
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<th>resolution</th> |
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<th>viewpoints</th> |
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<th>moments</th> |
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<th>intensities</th> |
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<th>image pairs</th> |
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</tr> |
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<tr> |
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<td style="vertical-align: middle;" rowspan="2">lane</td> |
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<td>training set</td> |
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<td style="vertical-align: middle;" rowspan="2">2048×1024</td> |
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<td>3</td> |
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<td style="vertical-align: middle;" rowspan="2">100</td> |
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<td style="vertical-align: middle;" rowspan="2">4</td> |
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<td>1200</td> |
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</tr> |
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<tr> |
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<td>test set</td> |
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<td>1</td> |
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<td>400</td> |
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</tr> |
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<tr> |
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<td style="vertical-align: middle;" rowspan="2">citystreet</td> |
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<td>training set</td> |
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<td style="vertical-align: middle;" rowspan="2">2048×1024</td> |
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<td>5</td> |
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<td style="vertical-align: middle;" rowspan="2">25</td> |
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<td style="vertical-align: middle;" rowspan="2">4</td> |
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<td>500</td> |
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</tr> |
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<tr> |
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<td>test set</td> |
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<td>1</td> |
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<td>100</td> |
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</tr> |
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<tr> |
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<td style="vertical-align: middle;" rowspan="2">japanesestreet</td> |
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<td>training set</td> |
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<td style="vertical-align: middle;" rowspan="2">2048×1024</td> |
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<td>8</td> |
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<td style="vertical-align: middle;" rowspan="2">25</td> |
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<td style="vertical-align: middle;" rowspan="2">4</td> |
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<td>800</td> |
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</tr> |
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<tr> |
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<td>test set</td> |
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<td>2</td> |
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<td>200</td> |
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</tr> |
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</table> |
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* `clean`: background RGB images and depth images of all scenes. |
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* `rainy`: rain layer images, RGB rainy images and depth rainy images of all scenes. |
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* `trainset.json`: the sample lists of the training set. |
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* `testset.json`: the sample lists of the test set. |
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* For each sample in the training set and the test set: |
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* `scene`: the scene name |
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* `sequence`: the viewpoint name |
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* `intensity`: the rain intensity |
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* `wind`: the wind direction( all zero for the HRI dataset) |
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* `background`: the path of the background RGB image |
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* `depth`: the path of the background depth image |
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* `rain_layer`: the path of the rain layer image |
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* `rainy_depth`: the path of the rainy depth image |
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* `rainy_image`: the path of the rainy RGB image |
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## BlenderFiles |
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The Blender files for rendering RGB and depth images of all viewpoints are included in the directory of each scene. |
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## Rain streak database |
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The Rain streak database from the paper [Rain Rendering for Evaluating and Improving Robustness to Bad Weather](https://github.com/astra-vision/rain-rendering). |
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## Ctation |
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When using these datasets, please cite our paper: |
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``` |
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@article{zhou2025high, |
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title={High-resolution Rainy Image Synthesis: Learning from Rendering}, |
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author={Zhou, Kaibin and Zhao, Shengjie and Deng, Hao and Zhang, Lin}, |
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journal={arXiv preprint arXiv:2502.16421}, |
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year={2025} |
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} |
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``` |