112 citations · 299 across the 9 of their papers we have counts for
17 papers
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.…
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
Shifeng Zhang, Cheng Chi, Yongqiang Yao +2
Object detection has been dominated by anchor-based detectors for several years. Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal Loss. In t…
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…
WiderPerson: A Diverse Dataset for Dense Pedestrian Detection in the Wild
Shifeng Zhang, Yiliang Xie, Jun Wan +3
Pedestrian detection has achieved significant progress with the availability of existing benchmark datasets. However, there is a gap in the diversity and density between real world…
Relational Learning for Joint Head and Human Detection
Cheng Chi, Shifeng Zhang, Junliang Xing +3
Head and human detection have been rapidly improved with the development of deep convolutional neural networks. However, these two tasks are often studied separately without consid…
PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes
Cheng Chi, Shifeng Zhang, Junliang Xing +3
Pedestrian detection in crowded scenes is a challenging problem, because occlusion happens frequently among different pedestrians. In this paper, we propose an effective and effici…