112 citations · 567 across the 18 of their papers we have counts for
18 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…
RefineFace: Refinement Neural Network for High Performance Face Detection
Shifeng Zhang, Cheng Chi, Zhen Lei +1
Face detection has achieved significant progress in recent years. However, high performance face detection still remains a very challenging problem, especially when there exists ma…
CASIA-SURF: A Large-scale Multi-modal Benchmark for Face Anti-spoofing
Shifeng Zhang, Ajian Liu, Jun Wan +5
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…
WIDER Face and Pedestrian Challenge 2018: Methods and Results
Chen Change Loy, Dahua Lin, Wanli Ouyang +49
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurat…
Improved Selective Refinement Network for Face Detection
Shifeng Zhang, Rui Zhu, Xiaobo Wang +5
As a long-standing problem in computer vision, face detection has attracted much attention in recent decades for its practical applications. With the availability of face detection…
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.…
Single-Shot Refinement Neural Network for Object Detection
Shifeng Zhang, Longyin Wen, Xiao Bian +2
For object detection, the two-stage approach (e.g., Faster R-CNN) has been achieving the highest accuracy, whereas the one-stage approach (e.g., SSD) has the advantage of high effi…
SFD: Single Shot Scale-invariant Face Detector
Shifeng Zhang, Xiangyu Zhu, Zhen Lei +3
This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (SFD), which performs superiorly on various scales of faces with a single deep ne…
FaceBoxes: A CPU Real-time Face Detector with High Accuracy
Shifeng Zhang, Xiangyu Zhu, Zhen Lei +3
Although tremendous strides have been made in face detection, one of the remaining open challenges is to achieve real-time speed on the CPU as well as maintain high performance, si…