Joint Segmentation and Identification Feature Learning for Occlusion Face Recognition

• Published in: IEEE transaction on neural networks and learning systems Vol. 34; no. 12; pp. 10875 - 10888
• Main Authors: Huang, Baojin, Wang, Zhongyuan, Jiang, Kui, Zou, Qin, Tian, Xin, Lu, Tao, Han, Zhen
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Datasets; Deep learning; Face; Face recognition; Facial Recognition; Feature extraction; Feature maps; Humans; Image Processing, Computer-Assisted; Image segmentation; Learning; Learning systems; Machine learning; Modules; Neural Networks, Computer; Occlusion; Occlusion face dataset; occlusion face recognition; occlusion segmentation; occlusion synthesis; Pattern recognition; Probability; Representation learning; Segmentation; Training

The existing occlusion face recognition algorithms almost tend to pay more attention to the visible facial components. However, these models are limited because they heavily rely on existing face segmentation approaches to locate occlusions, which is extremely sensitive to the performance of mask le...