8 citations · 13 across the 5 of their papers we have counts for
6 papers
A Scale-Arbitrary Image Super-Resolution Network Using Frequency-domain Information
Jing Fang, Yinbo Yu, Zhongyuan Wang +2
Image super-resolution (SR) is a technique to recover lost high-frequency information in low-resolution (LR) images. Spatial-domain information has been widely exploited to impleme…
Exploring Image Enhancement for Salient Object Detection in Low Light Images
Xin Xu, Shiqin Wang, Zheng Wang +2
Low light images captured in a non-uniform illumination environment usually are degraded with the scene depth and the corresponding environment lights. This degradation results in…
Person Re-Identification via Active Hard Sample Mining
Xin Xu, Lei Liu, Weifeng Liu +2
Annotating a large-scale image dataset is very tedious, yet necessary for training person re-identification models. To alleviate such a problem, we present an active hard sample mi…
Lossless Attention in Convolutional Networks for Facial Expression Recognition in the Wild
Chuang Wang, Ruimin Hu, Min Hu +5
Unlike the constraint frontal face condition, faces in the wild have various unconstrained interference factors, such as complex illumination, changing perspective and various occl…
Ensemble Super-Resolution with A Reference Dataset
Junjun Jiang, Yi Yu, Zheng Wang +3
By developing sophisticated image priors or designing deep(er) architectures, a variety of image Super-Resolution (SR) approaches have been proposed recently and achieved very prom…
TLR: Transfer Latent Representation for Unsupervised Domain Adaptation
Pan Xiao, Bo Du, Jia Wu +3
Domain adaptation refers to the process of learning prediction models in a target domain by making use of data from a source domain. Many classic methods solve the domain adaptatio…