Papers Single Image Deraining
“Single Image Deraining” 태그가 달린 논문 95편 · 필터 해제
DeRainMamba: A Frequency-Aware State Space Model with Detail Enhancement for Image Deraining
Image deraining is crucial for improving visual quality and supporting reliable downstream vision tasks. Although Mamba-based models provide efficient sequence modeling, their limited ability to capture fine-grained deta…
Single Image DerainingRain RemovalForward-only Diffusion Probabilistic Models
This work presents a forward-only diffusion (FoD) approach for generative modelling. In contrast to traditional diffusion models that rely on a coupled forward-backward diffusion scheme, FoD directly learns data generati…
Conditional Image GenerationImage DehazingImage GenerationImage Restoration+2Iterative Optimal Attention and Local Model for Single Image Rain Streak Removal
High-fidelity imaging is crucial for the successful safety supervision and intelligent deployment of vision-based measurement systems (VBMS). It ensures high-quality imaging in VBMS, which is fundamental for reliable vis…
Image ReconstructionRain RemovalSingle Image DerainingUnified Image Restoration and Enhancement: Degradation Calibrated Cycle Reconstruction Diffusion Model
Image restoration and enhancement are pivotal for numerous computer vision applications, yet unifying these tasks efficiently remains a significant challenge. Inspired by the iterative refinement capabilities of diffusio…
DenoisingImage DeblurringImage DehazingImage Inpainting+5A Hybrid Transformer-Mamba Network for Single Image Deraining
Existing deraining Transformers employ self-attention mechanisms with fixed-range windows or along channel dimensions, limiting the exploitation of non-local receptive fields. In response to this issue, we introduce a no…
MambaRain RemovalSingle Image DerainingAdaptive Frequency Enhancement Network for Single Image Deraining
Image deraining aims to improve the visibility of images damaged by rainy conditions, targeting the removal of degradation elements such as rain streaks, raindrops, and rain accumulation. While numerous single image dera…
Image EnhancementRain RemovalSingle Image DerainingCycle Contrastive Adversarial Learning for Unsupervised image Deraining
To tackle the difficulties in fitting paired real-world data for single image deraining (SID), recent unsupervised methods have achieved notable success. However, these methods often struggle to generate high-quality, ra…
Contrastive LearningGenerative Adversarial NetworkImage ReconstructionRain Removal+1Explore Internal and External Similarity for Single Image Deraining with Graph Neural Networks
Patch-level non-local self-similarity is an important property of natural images. However, most existing methods do not consider this property into neural networks for image deraining, thus affecting recovery performance…
Rain RemovalSingle Image DerainingGT-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. The aim of this competition is to study the rainy weather phenomenon in real world scenarios, provide …
Rain RemovalSingle Image DerainingGabor-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. While convolutional neural networks (CNNs) are popular, thei…
Rain RemovalSingle Image DerainingExploiting Regional Information Transformer for Single Image Deraining
Transformer-based Single Image Deraining (SID) methods have achieved remarkable success, primarily attributed to their robust capability in capturing long-range interactions. However, we've noticed that current methods h…
Image ReconstructionRain RemovalSingle Image DerainingDPAFNet:Dual Path Attention Fusion Network for Single Image Deraining
Rainy weather will have a significant impact on the regular operation of the imaging system. Based on this premise, image rain removal has always been a popular branch of low-level visual tasks, especially methods using …
Rain RemovalSingle Image DerainingExploring the potential of channel interactions for image restoration
Image restoration aims to reconstruct a clear image from a degraded observation. Convolutional neural networks have achieved promising performance on this task. The usage of Transformer has recently made significant adva…
DeblurringImage DeblurringImage Defocus DeblurringImage Dehazing+5Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge
Diffusion models exhibit powerful generative capabilities enabling noise mapping to data via reverse stochastic differential equations. However, in image restoration, the focus is on the mapping relationship from low-qua…
Image InpaintingImage RestorationImage Super-ResolutionRain Removal+2Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual Noise
Recently, research on denoising diffusion models has expanded its application to the field of image restoration. Traditional diffusion-based image restoration methods utilize degraded images as conditional input to effec…
DenoisingImage GenerationImage RestorationLow-Light Image Enhancement+2Controlling Vision-Language Models for Multi-Task Image Restoration
Vision-language models such as CLIP have shown great impact on diverse downstream tasks for zero-shot or label-free predictions. However, when it comes to low-level vision such as image restoration their performance dete…
Image DehazingImage DenoisingImage InpaintingImage Reconstruction+8Latent Degradation Representation Constraint for Single Image Deraining
Since rain streaks show a variety of shapes and directions, learning the degradation representation is extremely challenging for single image deraining. Existing methods are mainly targeted at designing complicated modul…
DecoderRain RemovalRepresentation LearningSingle Image DerainingPrompt-based Ingredient-Oriented All-in-One Image Restoration
Image restoration aims to recover the high-quality images from their degraded observations. Since most existing methods have been dedicated into single degradation removal, they may not yield optimal results on other typ…
AllDeblurringDecoderImage Deblurring+2Learning 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. However, existing approaches tend to integrate global features based o…
Image ReconstructionRain RemovalSingle Image DerainingFrom Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain Removal
Learning-based image deraining methods have made great progress. However, the lack of large-scale high-quality paired training samples is the main bottleneck to hamper the real image deraining (RID). To address this dile…
DiversityRain RemovalSingle Image Deraining