Dilated Convolution-based Feature Refinement Network for Crowd Localization
Gao, Xingyu1; Xie, Jinyang2; Chen, Zhenyu3,4; Liu, An-An5; Sun, Zhenan6,7; Lyu, Lei2
发表期刊ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
ISSN1551-6857
2023-11-01
卷号19期号:6页码:16
通讯作者Xie, Jinyang(xiejinyangsdnu@163.com) ; Lyu, Lei(lvlei@sdnu.edu.cn)
摘要As an emerging computer vision task, crowd localization has received increasing attention due to its ability to produce more accurate spatially predictions. However, continuous scale variations in complex crowd scenes lead to tiny individuals at the edges, so that existing methods cannot achieve precise crowd localization. Aiming at alleviating the above problems, we propose a novel Dilated Convolution-based Feature Refinement Network (DFRNet) to enhance the representation learning capability. Specifically, the DFRNet is built with three branches that can capture the information of each individual in crowd scenes more precisely. More specifically, we introduce a Feature Perception Module to model long-range contextual information at different scales by adopting multiple dilated convolutions, thus providing sufficient feature information to perceive tiny individuals at the edge of images. Afterwards, a Feature Refinement Module is deployed at multiple stages of the three branches to facilitate the mutual refinement of feature information at different scales, thus further improving the expression capability of multi-scale contextual information. By incorporating the above modules, DFRNet can locate individuals in complex scenes more precisely. Extensive experiments on multiple datasets demonstrate that the proposed method has more advanced performance compared to existing methods and can be more accurately adapted to complex crowd scenes.
关键词Dilated convolution Feature Refinement crowd localization contextual information
DOI10.1145/3571134
关键词[WOS]MEAN SQUARED ERROR
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[61976127] ; Science and Technology Innovation 2030-Major Project (Brain Science and Brain-Like Intelligence Technology)[2022ZD0208700]
项目资助者National Natural Science Foundation of China ; Science and Technology Innovation 2030-Major Project (Brain Science and Brain-Like Intelligence Technology)
WOS研究方向Computer Science
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS记录号WOS:001035785200039
出版者ASSOC COMPUTING MACHINERY
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/54003
专题多模态人工智能系统全国重点实验室
通讯作者Xie, Jinyang; Lyu, Lei
作者单位1.Chinese Acad Sci, Inst Microelect, Beijing, Peoples R China
2.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan, Peoples R China
3.State Grid Corp China, Big Data Ctr, Beijing, Peoples R China
4.China Elect Power Res Inst, Beijing, Peoples R China
5.Tianjin Univ, Sch Elect & Informat Engn, Tianjin, Peoples R China
6.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
7.Univ Chinese Acad Sci, Beijing, Peoples R China
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GB/T 7714
Gao, Xingyu,Xie, Jinyang,Chen, Zhenyu,et al. Dilated Convolution-based Feature Refinement Network for Crowd Localization[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2023,19(6):16.
APA Gao, Xingyu,Xie, Jinyang,Chen, Zhenyu,Liu, An-An,Sun, Zhenan,&Lyu, Lei.(2023).Dilated Convolution-based Feature Refinement Network for Crowd Localization.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,19(6),16.
MLA Gao, Xingyu,et al."Dilated Convolution-based Feature Refinement Network for Crowd Localization".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 19.6(2023):16.
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