Papers Video deraining
“Video deraining” 태그가 달린 논문 33편 · 필터 해제
UENR-600K: A Large-Scale Physically Grounded Dataset for Nighttime Video Deraining
Nighttime video deraining is uniquely challenging because raindrops interact with artificial lighting. Unlike daytime white rain, nighttime rain takes on various colors and appears locally illuminated. Existing small-sca…
Video GenerationVideo derainingZero-Shot Video Deraining with Video Diffusion Models
Existing video deraining methods are often trained on paired datasets, either synthetic, which limits their ability to generalize to real-world rain, or captured by static cameras, which restricts their effectiveness in …
Video derainingDeLiVR: Differential Spatiotemporal Lie Bias for Efficient Video Deraining
Videos captured in the wild often suffer from rain streaks, blur, and noise. In addition, even slight changes in camera pose can amplify cross-frame mismatches and temporal artifacts. Existing methods rely on optical flo…
Video derainingSemi-Supervised State-Space Model with Dynamic Stacking Filter for Real-World Video Deraining
Significant progress has been made in video restoration under rainy conditions over the past decade, largely propelled by advancements in deep learning. Nevertheless, existing methods that depend on paired data struggle …
object-detectionObject DetectionRain RemovalVideo deraining+1SpikeDerain: Unveiling Clear Videos from Rainy Sequences Using Color Spike Streams
Restoring clear frames from rainy videos presents a significant challenge due to the rapid motion of rain streaks. Traditional frame-based visual sensors, which capture scene content synchronously, struggle to capture th…
Rain RemovalVideo derainingLearning Truncated Causal History Model for Video Restoration
One key challenge to video restoration is to model the transition dynamics of video frames governed by motion. In this work, we propose TURTLE to learn the truncated causal history model for efficient and high-performing…
DeblurringDenoisingmodelRaindrop Removal+8RainMamba: Enhanced Locality Learning with State Space Models for Video Deraining
The outdoor vision systems are frequently contaminated by rain streaks and raindrops, which significantly degenerate the performance of visual tasks and multimedia applications. The nature of videos exhibits redundant te…
Optical Flow EstimationRain RemovalState Space ModelsVideo deraining+1A Two-Stage Adverse Weather Semantic Segmentation Method for WeatherProof Challenge CVPR 2024 Workshop UG2+
This technical report presents our team's solution for the WeatherProof Dataset Challenge: Semantic Segmentation in Adverse Weather at CVPR'24 UG2+. We propose a two-stage deep learning framework for this task. In the fi…
Rain RemovalSegmentationSemantic SegmentationVideo derainingNightRain: Nighttime Video Deraining via Adaptive-Rain-Removal and Adaptive-Correction
Existing deep-learning-based methods for nighttime video deraining rely on synthetic data due to the absence of real-world paired data. However, the intricacies of the real world, particularly with the presence of light …
Rain RemovalVideo derainingEGVD: Event-Guided Video Deraining
With the rapid development of deep learning, video deraining has experienced significant progress. However, existing video deraining pipelines cannot achieve satisfying performance for scenes with rain layers of complex …
Motion DetectionRain RemovalVideo derainingA Two-Stage Real Image Deraining Method for GT-RAIN Challenge CVPR 2023 Workshop UG$^{\textbf{2}}$+ Track 3
In this technical report, we briefly introduce the solution of our team HUST\li VIE for GT-Rain Challenge in CVPR 2023 UG$^{2}$+ Track 3. In this task, we propose an efficient two-stage framework to reconstruct a clear i…
Image RestorationRain RemovalSingle Image DerainingSSIM+1Event-Aware Video Deraining via Multi-Patch Progressive Learning
In this paper, we address the problem of video-based rain streak removal by developing an event-aware multi-patch progressive neural network. Rain streaks in video exhibit correlations in both temporal and spatial dimens…
Rain RemovalVideo derainingVideo Waterdrop Removal via Spatio-Temporal Fusion in Driving Scenes
The waterdrops on windshields during driving can cause severe visual obstructions, which may lead to car accidents. Meanwhile, the waterdrops can also degrade the performance of a computer vision system in autonomous dri…
Autonomous DrivingRaindrop RemovalVideo derainingUnsupervised Video Deraining with An Event Camera
Current unsupervised video deraining methods are inefficient in modeling the intricate spatio-temporal properties of rain, which leads to unsatisfactory results. In this paper, we propose a novel approach by integrat…
Contrastive LearningRain RemovalVideo deraining0/1 Deep Neural Networks via Block Coordinate Descent
The step function is one of the simplest and most natural activation functions for deep neural networks (DNNs). As it counts 1 for positive variables and 0 for others, its intrinsic characteristics (e.g., discontinuity a…
10-shot image generation16k2D Object Detection+92Recurrent Video Restoration Transformer with Guided Deformable Attention
Video restoration aims at restoring multiple high-quality frames from multiple low-quality frames. Existing video restoration methods generally fall into two extreme cases, i.e., they either restore all frames in paralle…
Analog Video RestorationDeblurringDenoisingSnow Removal+5Learning Trajectory-Aware Transformer for Video Super-Resolution
Video super-resolution (VSR) aims to restore a sequence of high-resolution (HR) frames from their low-resolution (LR) counterparts. Although some progress has been made, there are grand challenges to effectively utilize …
Super-ResolutionVideo derainingVideo Super-ResolutionNeural Compression-Based Feature Learning for Video Restoration
How to efficiently utilize the temporal features is crucial, yet challenging, for video restoration. The temporal features usually contain various noisy and uncorrelated information, and they may interfere with the resto…
DenoisingQuantizationRain RemovalVideo Denoising+2Uncertainty-Aware Cascaded Dilation Filtering for High-Efficiency Deraining
Deraining is a significant and fundamental computer vision task, aiming to remove the rain streaks and accumulations in an image or video captured under a rainy day. Existing deraining methods usually make heuristic assu…
Data AugmentationRain RemovalSingle Image DerainingVideo deraining+1Restormer: 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. Recently, another c…
Color Image DenoisingDeblurringDenoisingGrayscale Image Denoising+10