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
Latest papers
KBNet: Kernel Basis Network for Image Restoration
zhangyi-3/kbnet
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In this paper, we propose a kernel basis attention (KBA) module, which introduces learnable kernel bases to model representative image patterns for spatial information aggregation.
Mixed Hierarchy Network for Image Restoration
tombs98/mhnet
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Our main proposal is a mixed hierarchy architecture, that progressively recovers contextual information and spatial details from degraded images while we design intra-blocks to reduce system complexity.
Image Restoration with Mean-Reverting Stochastic Differential Equations
algolzw/image-restoration-sde
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This paper presents a stochastic differential equation (SDE) approach for general-purpose image restoration.
Not Just Streaks: Towards Ground Truth for Single Image Deraining
UCLA-VMG/GT-RAIN
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We propose a large-scale dataset of real-world rainy and clean image pairs and a method to remove degradations, induced by rain streaks and rain accumulation, from the image.
Toward Real-world Single Image Deraining: A New Benchmark and Beyond
To address these issues, we establish a new high-quality dataset named RealRain-1k, consisting of $1, 120$ high-resolution paired clean and rainy images with low- and high-density rain streaks, respectively.
DRT: A Lightweight Single Image Deraining Recursive Transformer
yc-liang/drt
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Over parameterization is a common technique in deep learning to help models learn and generalize sufficiently to the given task; nonetheless, this often leads to enormous network structures and consumes considerable computing resources during training.
On Representation Learning with Feedback
This note complements the author's recent paper "Robust representation learning with feedback for single image deraining" by providing heuristically theoretical explanations on the mechanism of representation learning with feedback, namely an essential merit of the works presented in this recent article.
Task Adaptive Network for Image Restoration With Combined Degradation Factors
JingyuanZhou/Task_Adaptive_Network
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IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) 2022
Therefore, we propose a task-adaptive attention module to enable the network to restore images with multiple degradation factors.
MAXIM: Multi-Axis MLP for Image Processing
google-research/maxim
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CVPR 2022
In this work, we present a multi-axis MLP based architecture called MAXIM, that can serve as an efficient and flexible general-purpose vision backbone for image processing tasks.
Uncertainty-Aware Cascaded Dilation Filtering for High-Efficiency Deraining
First, we propose the uncertainty-aware cascaded predictive filtering (UC-PFilt) that can identify the difficulties of reconstructing clean pixels via predicted kernels and remove the residual rain traces effectively.
