52 citations · 84 across the 4 of their papers we have counts for
6 papers
Unfolded Deep Kernel Estimation for Blind Image Super-resolution
Hongyi Zheng, Hongwei Yong, Lei Zhang
Blind image super-resolution (BISR) aims to reconstruct a high-resolution image from its low-resolution counterpart degraded by unknown blur kernel and noise. Many deep neural netw…
Gradient Centralization: A New Optimization Technique for Deep Neural Networks
Hongwei Yong, Jianqiang Huang, Xiansheng Hua +1
Optimization techniques are of great importance to effectively and efficiently train a deep neural network (DNN). It has been shown that using the first and second order statistics…
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…
Model Inconsistent but Correlated Noise: Multi-view Subspace Learning with Regularized Mixture of Gaussians
Hongwei Yong, Deyu Meng, Jinxing Li +2
Multi-view subspace learning (MSL) aims to find a low-dimensional subspace of the data obtained from multiple views. Different from single view case, MSL should take both common an…
Sharp Attention Network via Adaptive Sampling for Person Re-identification
Chen Shen, Guo-Jun Qi, Rongxin Jiang +4
In this paper, we present novel sharp attention networks by adaptively sampling feature maps from convolutional neural networks (CNNs) for person re-identification (re-ID) problem.…
Robust Online Matrix Factorization for Dynamic Background Subtraction
Hongwei Yong, Deyu Meng, Wangmeng Zuo +1
We propose an effective online background subtraction method, which can be robustly applied to practical videos that have variations in both foreground and background. Different fr…