Single Image Deraining
50 papers with code • 9 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Single Image Deraining
Libraries
Use these libraries to find Single Image Deraining models and implementations
Raindrop
Synthetic Rain Datasets
RainCityscapes
Real Rain Dataset
Most implemented papers
Restormer: Efficient Transformer for High-Resolution Image Restoration
Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration and related tasks.
Multi-Stage Progressive Image Restoration
At each stage, we introduce a novel per-pixel adaptive design that leverages in-situ supervised attention to reweight the local features.
Pre-Trained Image Processing Transformer
huawei-noah/Pretrained-IPT
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CVPR 2021
To maximally excavate the capability of transformer, we present to utilize the well-known ImageNet benchmark for generating a large amount of corrupted image pairs.
Progressive Image Deraining Networks: A Better and Simpler Baseline
To handle this issue, this paper provides a better and simpler baseline deraining network by considering network architecture, input and output, and loss functions.
NASNet: A Neuron Attention Stage-by-Stage Net for Single Image Deraining
In this paper, we propose a novel end-to-end Neuron Attention Stage-by-Stage Net (NASNet), which can solve all types of rain model tasks efficiently.
Multi-Scale Progressive Fusion Network for Single Image Deraining
In this work, we explore the multi-scale collaborative representation for rain streaks from the perspective of input image scales and hierarchical deep features in a unified framework, termed multi-scale progressive fusion network (MSPFN) for single image rain streak removal.
SDNet: mutil-branch for single image deraining using swin
The former implements the basic rain pattern feature extraction, while the latter fuses different features to further extract and process the image features.
Clearing the Skies: A deep network architecture for single-image rain removal
jinnovation/rainy-image-dataset
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We introduce a deep network architecture called DerainNet for removing rain streaks from an image.
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset
stevewongv/SPANet
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CVPR 2019
Second, to better cover the stochastic distribution of real rain streaks, we propose a novel SPatial Attentive Network (SPANet) to remove rain streaks in a local-to-global manner.
EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining
To fill this gap, in this paper, we regard the single-image deraining as a general image-enhancing problem and originally propose a model-free deraining method, i. e., EfficientDeRain, which is able to process a rainy image within 10~ms (i. e., around 6~ms on average), over 80 times faster than the state-of-the-art method (i. e., RCDNet), while achieving similar de-rain effects.
