activity
20122023
most citedBeyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

9.2k citations · 12.1k across the 87 of their papers we have counts for

collaborators
Showing 2019Show all

6 papers · 1 filter

eess.IV2019★ 71 cited

A Survey on Rain Removal from Video and Single Image

Hong Wang, Yichen Wu, Minghan Li +2

Rain streaks might severely degenerate the performance of video/image processing tasks. The investigations on rain removal from video or a single image has thus been attracting muc…

cs.CV2019★ 4 cited

Video Rain/Snow Removal by Transformed Online Multiscale Convolutional Sparse Coding

Minghan Li, Xiangyong Cao, Qian Zhao +3

Video rain/snow removal from surveillance videos is an important task in the computer vision community since rain/snow existed in videos can severely degenerate the performance of…

cs.CV2019★ 212 cited

Variational Denoising Network: Toward Blind Noise Modeling and Removal

Zongsheng Yue, Hongwei Yong, Qian Zhao +2

Blind image denoising is an important yet very challenging problem in computer vision due to the complicated acquisition process of real images. In this work we propose a new varia…

cs.LG2019★ 398 cited

Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting

Jun Shu, Qi Xie, Lixuan Yi +4

Current deep neural networks (DNNs) can easily overfit to biased training data with corrupted labels or class imbalance. Sample re-weighting strategy is commonly used to alleviate…

cs.CV2019★ 19 cited

Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net

Qi Xie, Minghao Zhou, Qian Zhao +3

Hyperspectral imaging can help better understand the characteristics of different materials, compared with traditional image systems. However, only high-resolution multispectral (H…

cs.CV2019★ 16 cited

Progressive Image Deraining Networks: A Better and Simpler Baseline

Dongwei Ren, Wangmeng Zuo, Qinghua Hu +2

Along with the deraining performance improvement of deep networks, their structures and learning become more and more complicated and diverse, making it difficult to analyze the co…