Rain Removal
124 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find Rain Removal models and implementations
Raindrop
Real Rain Dataset
RainDS
LasVR
Latest papers with no code
FreqMamba: Viewing Mamba from a Frequency Perspective for Image Deraining
Recent studies have witnessed the effectiveness and efficiency of Mamba for perceiving global and local information based on its exploiting local correlation among patches, however, rarely attempts have been explored to extend it with frequency analysis for image deraining, limiting its ability to perceive global degradation that is relevant to frequency modeling (e. g. Fourier transform).
Specularity Factorization for Low-Light Enhancement
We present a new additive image factorization technique that treats images to be composed of multiple latent specular components which can be simply estimated recursively by modulating the sparsity during decomposition.
IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions
Recent advances have demonstrated the powerful capability of transformer architecture in image restoration.
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.
