Mingze Li, Diwen Zheng, Shuhua Lu*
CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2105-2122, 2024, DOI:10.32604/cmc.2024.048928
Abstract Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis, achieving tremendous success recently with the development of deep learning. However, there have been still many challenges including crowd multi-scale variations and high network complexity, etc. To tackle these issues, a lightweight Res-connection multi-branch network (LRMBNet) for highly accurate crowd counting and localization is proposed. Specifically, using improved ShuffleNet V2 as the backbone, a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters. A light multi-branch structure with different expansion rate… More >
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