GTAV-NightRain: Photometric Realistic Large-scale Dataset for Night-time Rain Streak Removal
Not on the map. Why?
Abstract (arXiv)
Rain is transparent, which reflects and refracts light in the scene to the camera. In outdoor vision, rain, especially rain streaks degrade visibility and therefore need to be removed. In existing rain streak removal datasets, although density, scale, direction and intensity have been considered, transparency is not fully taken into account. This problem is particularly serious in night scenes, where the appearance of rain largely depends on the interaction with scene illuminations and changes drastically on different positions within the image. This is problematic, because unrealistic dataset causes serious domain bias. In this paper, we propose GTAV-NightRain dataset, which is a large-scale synthetic night-time rain streak removal dataset. Unlike existing datasets, by using 3D computer graphic platform (namely GTA V), we are allowed to infer the three dimensional interaction between rain and illuminations, which insures the photometric realness. Current release of the dataset contains 12,860 HD rainy images and 1,286 corresponding HD ground truth images in diversified night scenes. A systematic benchmark and analysis are provided along with the dataset to inspire further research.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 22 of its 49 references that are in the map. First posted on arXiv 10 Oct 2022.
Builds on
22 of 49 references.
References · 22
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10 more
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Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 4; 2026: 3.
9 papers.
- 2023Atlantis: Enabling Underwater Depth Estimation with Stable Diffusioncited by 28
- 2025Channel Consistency Prior and Self-Reconstruction Strategy Based Unsupervised Image Derainingcited by 11
- 2025Rethinking Nighttime Image Deraining via Learnable Color Space Transformationcited by 5
- 2025Clear Nights Ahead: Towards Multi-Weather Nighttime Image Restorationcited by 2
- 2026UniRain: Unified Image Deraining with RAG-based Dataset Distillation and Multi-objective Reweighted Optimizationcited by 2
- 2024Is That Rain? Understanding Effects on Visual Odometry Performance for Autonomous UAVs and Efficient DNN-based Rain Classification at the Edgecited by 1
- 2026UENR-600K: A Large-Scale Physically Grounded Dataset for Nighttime Video Derainingcited by 1
- 2025NDLPNet: A Location-Aware Nighttime Deraining Network and a Real-World Benchmark Datasetcited by 0
- 2026DerainSplat: Feed-Forward Clean 3D Gaussian Splatting from Sparse Rainy Viewscited by 0
- 2026DerainSplat: Feed-Forward Clean 3D Gaussian Splatting from Sparse Rainy Views3 Aug 2026
- 2026UENR-600K: A Large-Scale Physically Grounded Dataset for Nighttime Video Deraining6 Apr 2026
- 2026UniRain: Unified Image Deraining with RAG-based Dataset Distillation and Multi-objective Reweighted Optimization4 Mar 2026
- 2025Rethinking Nighttime Image Deraining via Learnable Color Space Transformation20 Oct 2025
- 2025NDLPNet: A Location-Aware Nighttime Deraining Network and a Real-World Benchmark Dataset17 Sep 2025
- 2025Clear Nights Ahead: Towards Multi-Weather Nighttime Image Restoration22 May 2025
- 2025Channel Consistency Prior and Self-Reconstruction Strategy Based Unsupervised Image Deraining24 Mar 2025
- 2024Is That Rain? Understanding Effects on Visual Odometry Performance for Autonomous UAVs and Efficient DNN-based Rain Classification at the Edge17 Jul 2024
- 2023Atlantis: Enabling Underwater Depth Estimation with Stable Diffusion19 Dec 2023