9.2k citations · 17.8k across the 63 of their papers we have counts for
8 papers · 1 filter
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…
Reliable and Efficient Image Cropping: A Grid Anchor based Approach
Hui Zeng, Lida Li, Zisheng Cao +1
Image cropping aims to improve the composition as well as aesthetic quality of an image by removing extraneous content from it. Existing image cropping databases provide only one o…
A Benchmark for Edge-Preserving Image Smoothing
Feida Zhu, Zhetong Liang, Xixi Jia +2
Edge-preserving image smoothing is an important step for many low-level vision problems. Though many algorithms have been proposed, there are several difficulties hindering its fur…
Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization
Qilong Wang, Jiangtao Xie, Wangmeng Zuo +2
Compared with global average pooling in existing deep convolutional neural networks (CNNs), global covariance pooling can capture richer statistics of deep features, having potenti…
Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model
Jianrui Cai, Hui Zeng, Hongwei Yong +2
Most of the existing learning-based single image superresolution (SISR) methods are trained and evaluated on simulated datasets, where the low-resolution (LR) images are generated…
Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels
Kai Zhang, Wangmeng Zuo, Lei Zhang
While deep neural networks (DNN) based single image super-resolution (SISR) methods are rapidly gaining popularity, they are mainly designed for the widely-used bicubic degradation…