A Weakly Supervised Hybrid Lightweight Network for Efficient Crowd Counting
Yongqi Chen,
Huailin Zhao,
Ming Gao
et al.
Abstract:Crowd-counting networks have become the mainstream method to deploy crowd-counting techniques on resource-constrained devices. Significant progress has been made in this field, with many outstanding lightweight models being proposed successively. However, challenges like scare-variation, global feature extraction, and fine-grained head annotation requirements still exist in relevant tasks, necessitating further improvement. In this article, we propose a weakly supervised hybrid lightweight crowd-counting netwo… Show more
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