SA-InterNet: Scale-Aware Interaction Network for Joint Crowd Counting and Localization

Xiuqi Chen, Xiao Yu, Huijun Di*, Shunzhou Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Crowd counting and crowd localization are essential and challenging tasks due to uneven distribution and scale variation. Recent studies have shown that crowd counting and localization can complement and guide each other from two different perspectives of crowd distribution. How to learn the complementary information is still a challenging problem. To this end, we propose a Scale-aware Interaction Network (SA-InterNet) for joint crowd counting and localization. We design a dual-branch network to regress the density map and the localization map, respectively. The dual-branch network is mainly constructed with scale-aware feature extractors, which can obtain multi-scale features. To achieve mutual guidance and assistance of the two tasks, we design a density-localization interaction module by learning the complementary information. Our SA-InterNet can obtain accurate density map and localization map of an input image. We conduct extensive experiments on three challenging crowd counting datasets, including ShanghaiTech Part_A, ShanghaiTech Part_B and UCF-QNRF. Our SA-InterNet achieves superior performance to state-of-the-art methods.

Original languageEnglish
Title of host publicationPattern Recognition and Computer Vision - 4th Chinese Conference, PRCV 2021, Proceedings
EditorsHuimin Ma, Liang Wang, Changshui Zhang, Fei Wu, Tieniu Tan, Yaonan Wang, Jianhuang Lai, Yao Zhao
PublisherSpringer Science and Business Media Deutschland GmbH
Pages203-215
Number of pages13
ISBN (Print)9783030880033
DOIs
Publication statusPublished - 2021
Event4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021 - Beijing, China
Duration: 29 Oct 20211 Nov 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13019 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021
Country/TerritoryChina
CityBeijing
Period29/10/211/11/21

Keywords

  • Crowd counting
  • Crowd localization
  • Multi-scale feature learning
  • Mutual learning

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