Title
NSSNet: Scale-Aware Object Counting With Non-Scale Suppression
Abstract
In object counting, objects often exhibit different sizes at different scales, even if they have similar physical sizes in reality. This is particularly true when targeting crowd counting and vehicle counting in intelligent transportation. Failing to model such variations leads to the mismatch between the object size and image scale. To address this problem, existing methods often extract multi-sc...
Year
DOI
Venue
2022
10.1109/TITS.2020.3030781
IEEE Transactions on Intelligent Transportation Systems
Keywords
DocType
Volume
Feature extraction,Transportation,Estimation,Fuses,Monitoring,Task analysis
Journal
23
Issue
ISSN
Citations 
4
1524-9050
0
PageRank 
References 
Authors
0.34
34
5
Name
Order
Citations
PageRank
Liang Liu116340.93
Zhiguo Cao231444.17
Hao Lu314020.86
Haipeng Xiong400.34
Chunhua Shen54817234.19