Self-supervised video representation learning by uncovering spatio-temporal statistics

• Main Authors: WANG, Jiangliu, JIAO, Jianbo, BAO, Linchao, HE, Shengfeng, LIU, Wei, LIU, Yun-hui
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Task analysis; Three-dimensional displays; Neural networks; Image color analysis; Visualization; Training; Feature extraction; Self-supervised learning; representation learning; video understanding; 3D CNN; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/7839; https://ink.library.smu.edu.sg/context/sis_research/article/8842/viewcontent/self_supervised.pdf
• Institution: Singapore Management University

This paper proposes a novel pretext task to address the self-supervised video representation learning problem. Specifically, given an unlabeled video clip, we compute a series of spatio-temporal statistical summaries, such as the spatial location and dominant direction of the largest motion, the spa...