Crowd counting via cross-stage refinement networks

• Main Authors: LIU, Yongtuo, WEN, Qiang, CHEN, Haoxin, LIU, Wenxi, QIN, Jing, HAN, Guoqiang, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Feature extraction; Convolution; Decoding; Clutter; Benchmark testing; Cameras; Network architecture; Crowd counting; recurrent network; image refinement; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/7848
• Institution: Singapore Management University

Crowd counting is challenging due to unconstrained imaging factors, e.g., background clutters, non-uniform distribution of people, large scale and perspective variations. Dealing with these problems using deep neural networks requires rich prior knowledge and multi-scale contextual representations....