112 citations · 567 across the 18 of their papers we have counts for
5 papers · 1 filter
Support Vector Guided Softmax Loss for Face Recognition
Xiaobo Wang, Shuo Wang, Shifeng Zhang +3
Face recognition has witnessed significant progresses due to the advances of deep convolutional neural networks (CNNs), the central challenge of which, is feature discrimination. T…
A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing
Shifeng Zhang, Xiaobo Wang, Ajian Liu +6
Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmar…
Selective Refinement Network for High Performance Face Detection
Cheng Chi, Shifeng Zhang, Junliang Xing +3
High performance face detection remains a very challenging problem, especially when there exists many tiny faces. This paper presents a novel single-shot face detector, named Selec…
Occlusion-aware R-CNN: Detecting Pedestrians in a Crowd
Shifeng Zhang, Longyin Wen, Xiao Bian +2
Pedestrian detection in crowded scenes is a challenging problem since the pedestrians often gather together and occlude each other. In this paper, we propose a new occlusion-aware…
Ensemble Soft-Margin Softmax Loss for Image Classification
Xiaobo Wang, Shifeng Zhang, Zhen Lei +3
Softmax loss is arguably one of the most popular losses to train CNN models for image classification. However, recent works have exposed its limitation on feature discriminability.…