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
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.
Dynamic Association Learning of Self-Attention and Convolution in Image Restoration
Thus, we propose to refine background textures with the predicted degradation prior in an association learning manner.
Towards Unified Deep Image Deraining: A Survey and A New Benchmark
In this paper, we provide a comprehensive review of existing image deraining method and provide a unify evaluation setting to evaluate the performance of image deraining methods.
Multi-dimension Queried and Interacting Network for Stereo Image Deraining
This module leverages dimension-wise queries that are independent of the input features and employs global context-aware attention (GCA) to capture essential features while avoiding the entanglement of redundant or irrelevant information.
Learning Image Deraining Transformer Network with Dynamic Dual Self-Attention
Recently, Transformer-based architecture has been introduced into single image deraining task due to its advantage in modeling non-local information.
Towards General and Fast Video Derain via Knowledge Distillation
As a common natural weather condition, rain can obscure video frames and thus affect the performance of the visual system, so video derain receives a lot of attention.
A Hybrid CNN-Transformer Architecture with Frequency Domain Contrastive Learning for Image Deraining
Image deraining is a challenging task that involves restoring degraded images affected by rain streaks.
Decomposition Ascribed Synergistic Learning for Unified Image Restoration
Learning to restore multiple image degradations within a single model is quite beneficial for real-world applications.
