Face detection is an ultimate component to support various visual facial related tasks. However, detecting faces with extremely low resolution or high occlusion is still an open problem. In this paper, we propose a two-step general approach to refine the performance of modern face detectors according to human's high-level context-aware ability. First, we propose Score-specific Non-Maximum Suppression (SNMS) to preserve overlapped faces. Second, we consider the coexistence prior among faces in the scene, which could raise the sensitivity of face detection in the crowd. When integrating our approach to the existing face detectors, most of them have better results on a challenging benchmark (WIDER FACE) and a newly proposed dataset (Faces in Crowd, FIC) made by us. Codes are available on https://github.com/AIoTP/SNMSandCoexistence.
|Title of host publication||2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|Publication status||Published - 17 Apr 2019|
|Event||44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom|
Duration: 12 May 2019 → 17 May 2019
|Name||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|Conference||44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019|
|Period||12/05/2019 → 17/05/2019|
Bibliographical noteFunding Information:
Thiswork issupported bythe NationalKeyR&D Program of China under Grant 2017YFB0802300, the National Natural Science Foundation of China (Grants No 61601223， 61801242), the Natural Science Foundation of Jiangsu Province (Grants No BK20150756)，China Postdoctoral Science Foundation (Grants No 2015M580427)，and the Fundamental Research Funds for the Central Universities ( No. NS2016091).
© 2019 IEEE.
Copyright 2019 Elsevier B.V., All rights reserved.
- Coexistence prior
- Contextual information
- Face detection
- Score-specific NMS
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering