14 citations · 14 across the 3 of their papers we have counts for
8 papers
Cross-Domain Similarity Learning for Face Recognition in Unseen Domains
Masoud Faraki, Xiang Yu, Yi-Hsuan Tsai +2
Face recognition models trained under the assumption of identical training and test distributions often suffer from poor generalization when faced with unknown variations, such as…
Improving Face Recognition by Clustering Unlabeled Faces in the Wild
Aruni RoyChowdhury, Xiang Yu, Kihyuk Sohn +2
While deep face recognition has benefited significantly from large-scale labeled data, current research is focused on leveraging unlabeled data to further boost performance, reduci…
Towards Universal Representation Learning for Deep Face Recognition
Yichun Shi, Xiang Yu, Kihyuk Sohn +2
Recognizing wild faces is extremely hard as they appear with all kinds of variations. Traditional methods either train with specifically annotated variation data from target domain…
DAVID: Dual-Attentional Video Deblurring
Junru Wu, Xiang Yu, Ding Liu +2
Blind video deblurring restores sharp frames from a blurry sequence without any prior. It is a challenging task because the blur due to camera shake, object movement and defocusing…
Pose-variant 3D Facial Attribute Generation
Feng-Ju Chang, Xiang Yu, Ram Nevatia +1
We address the challenging problem of generating facial attributes using a single image in an unconstrained pose. In contrast to prior works that largely consider generation on 2D…
Feature Transfer Learning for Deep Face Recognition with Under-Represented Data
Xi Yin, Xiang Yu, Kihyuk Sohn +2
Despite the large volume of face recognition datasets, there is a significant portion of subjects, of which the samples are insufficient and thus under-represented. Ignoring such s…