Glance to count: Learning to rank with anchors for weakly-supervised crowd counting

• Main Authors: XIONG, Zheng, CHAI, Liangyu, LIU, Wenxi, LIU, Yongtuo, REN, Sucheng, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Crowd Counting; Weakly-supervised Learning; Ranking; Graphics and Human Computer Interfaces; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/8533; https://ink.library.smu.edu.sg/context/sis_research/article/9536/viewcontent/GlancetoCount_av__2_.pdf
• Institution: Singapore Management University

Crowd image is arguably one of the most laborious data to annotate. In this paper, we devote to reduce the massive demand of densely labeled crowd data, and propose a novel weakly-supervised setting, in which we leverage the binary ranking of two images with highcontrast crowd counts as training gui...