Unsupervised video hashing with multi-granularity contextualization and multi-structure preservation

• Main Authors: HAO, Yanbin, DUAN, Jingru, ZHANG, Hao, ZHU, Bin, ZHOU, Pengyuan, HE, Xiangnan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Hashing; feature contextualization; unsupervised learning; video retrieval; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/9014; https://ink.library.smu.edu.sg/context/sis_research/article/10017/viewcontent/mm22_video_hashing.pdf
• Institution: Singapore Management University

Unsupervised video hashing typically aims to learn a compact binary vector to represent complex video content without using manual annotations. Existing unsupervised hashing methods generally suffer from incomplete exploration of various perspective dependencies (e.g., long-range and short-range) an...