5 citations · 7 across the 3 of their papers we have counts for
5 papers · 1 filter
Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment
Jia Guo, Jiankang Deng, Niannan Xue +1
Facial landmark localisation in images captured in-the-wild is an important and challenging problem. The current state-of-the-art revolves around certain kinds of Deep Convolutiona…
Side Information for Face Completion: a Robust PCA Approach
Niannan Xue, Jiankang Deng, Shiyang Cheng +2
Robust principal component analysis (RPCA) is a powerful method for learning low-rank feature representation of various visual data. However, for certain types as well as significa…
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Jiankang Deng, Jia Guo, Jing Yang +3
Recently, a popular line of research in face recognition is adopting margins in the well-established softmax loss function to maximize class separability. In this paper, we first i…
UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition
Jiankang Deng, Shiyang Cheng, Niannan Xue +2
Recently proposed robust 3D face alignment methods establish either dense or sparse correspondence between a 3D face model and a 2D facial image. The use of these methods presents…
Side Information in Robust Principal Component Analysis: Algorithms and Applications
Niannan Xue, Yannis Panagakis, Stefanos Zafeiriou
Robust Principal Component Analysis (RPCA) aims at recovering a low-rank subspace from grossly corrupted high-dimensional (often visual) data and is a cornerstone in many machine l…