Rain Removal
122 papers with code • 1 benchmarks • 4 datasets
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Use these libraries to find Rain Removal models and implementationsLatest papers with no code
Image Deraining via Self-supervised Reinforcement Learning
The work aims to recover rain images by removing rain streaks via Self-supervised Reinforcement Learning (RL) for image deraining (SRL-Derain).
Distilling Semantic Priors from SAM to Efficient Image Restoration Models
SPD leverages a self-distillation manner to distill the fused semantic priors to boost the performance of original IR models.
GT-Rain Single Image Deraining Challenge Report
This report reviews the results of the GT-Rain challenge on single image deraining at the UG2+ workshop at CVPR 2023.
TRG-Net: An Interpretable and Controllable Rain Generator
Our unpaired generation experiments demonstrate that the rain generated by the proposed rain generator is not only of higher quality, but also more effective for deraining and downstream tasks compared to current state-of-the-art rain generation methods.
Gabor-guided transformer for single image deraining
Image deraining have have gained a great deal of attention in order to address the challenges posed by the effects of harsh weather conditions on visual tasks.
Boosting Image Restoration via Priors from Pre-trained Models
Pre-trained models with large-scale training data, such as CLIP and Stable Diffusion, have demonstrated remarkable performance in various high-level computer vision tasks such as image understanding and generation from language descriptions.
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style Transfer
By leveraging the flexibility of ConStyle, we develop a \textbf{general restoration network} for image restoration.
DPAFNet:Dual Path Attention Fusion Network for Single Image Deraining
Rainy weather will have a significant impact on the regular operation of the imaging system.
NightRain: Nighttime Video Deraining via Adaptive-Rain-Removal and Adaptive-Correction
However, the intricacies of the real world, particularly with the presence of light effects and low-light regions affected by noise, create significant domain gaps, hampering synthetic-trained models in removing rain streaks properly and leading to over-saturation and color shifts.
End-to-end Rain Streak Removal with RAW Images
To be specific, we generate rainy RAW data by converting color rain streak into RAW space and design simple but efficient RAW processing algorithms to synthesize both rainy and clean color images.