Learning disentangled representation implicitly via transformer for occluded person re-identification

• Main Authors: Jia, Mengxi, Cheng, Xinhua, Lu, Shijian, Zhang, Jian
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Person Re-Identification; Representation Learning
• Online Access: https://hdl.handle.net/10356/162960
• Institution: Nanyang Technological University

Person re-IDentification (re-ID) under various occlusions has been a long-standing challenge as person images with different types of occlusions often suffer from misalignment in image matching and ranking. Most existing methods tackle this challenge by aligning spatial features of body parts accord...