WIDER FACE: A Face Detection Benchmark
Chinese University of Hong Kong · Shenzhen Institutes of Advanced Technology
Abstract
Face detection is one of the most studied topics in the computer vision community. Much of the progresses have been made by the availability of face detection benchmark datasets. We show that there is a gap between current face detection performance and the real world requirements. To facilitate future face detection research, we introduce the WIDER FACE dataset1, which is 10 times larger than existing datasets. The dataset contains rich annotations, including occlusions, poses, event categories, and face bounding boxes. Faces in the proposed dataset are extremely challenging due to large variations in scale, pose and occlusion, as shown in Fig. 1. Furthermore, we show that WIDER FACE dataset is an effective…
Citation impact
- FWCI
- 73.49
- Percentile
- 100%
- References
- 43
Authors
4- SYShuo YangCorresponding
Chinese University of Hong Kong
- PLPing Luo
Chinese University of Hong Kong, Shenzhen Institutes of Advanced Technology
- CCChen Change Loy
Chinese University of Hong Kong, Shenzhen Institutes of Advanced Technology
- XTXiaoou Tang
Shenzhen Institutes of Advanced Technology, Chinese University of Hong Kong
Topics & keywords
- Benchmark (surveying)
- Computer science
- Face (sociological concept)
- Face detection
- Artificial intelligence
- Bounding overwatch
- Object-class detection
- Facial recognition system