Toward a Comprehensive Face Detector in the Wild

• Published in: IEEE transactions on circuits and systems for video technology Vol. 29; no. 1; pp. 104 - 114
• Main Authors: Li, Jianshu, Liu, Luoqi, Li, Jianan, Feng, Jiashi, Yan, Shuicheng, Sim, Terence
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Bi-channel architecture; blur-aware; Critical components; Datasets; Deformation mechanisms; Detectors; Face; Face detection; Face recognition; Feature extraction; Harvesting; Learning; Neural networks; Proposals; State of the art; Training; video context

In this paper, we aim to build a comprehensive face detection system which provides a one-stop solution to various practical challenges for face detection in realistic scenarios, e.g., detecting faces from multiple-views, faces with occlusions, exaggerated expressions or blurred faces. Moreover, we...