29 citations · 93 across the 7 of their papers we have counts for
8 papers · 1 filter
PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition
Qiang Meng, Xiaqing Xu, Xiaobo Wang +6
Despite the great success achieved by deep learning methods in face recognition, severe performance drops are observed for large pose variations in unconstrained environments (e.g.…
Loss Function Search for Face Recognition
Xiaobo Wang, Shuo Wang, Cheng Chi +2
In face recognition, designing margin-based (e.g., angular, additive, additive angular margins) softmax loss functions plays an important role in learning discriminative features.…
Mis-classified Vector Guided Softmax Loss for Face Recognition
Xiaobo Wang, Shifeng Zhang, Shuo Wang +3
Face recognition has witnessed significant progress due to the advances of deep convolutional neural networks (CNNs), the central task of which is how to improve the feature discri…
A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark
Yinglu Liu, Hailin Shi, Yue Si +3
Face parsing, which is to assign a semantic label to each pixel in face images, has recently attracted increasing interest due to its huge application potentials. Although many fac…
Grand Challenge of 106-Point Facial Landmark Localization
Yinglu Liu, Hao Shen, Yue Si +18
Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, pre…
Prediction-Tracking-Segmentation
Jianren Wang, Yihui He, Xiaobo Wang +2
We introduce a prediction driven method for visual tracking and segmentation in videos. Instead of solely relying on matching with appearance cues for tracking, we build a predicti…