Weakly-Supervised Scene-Specific Crowd Counting Using Real-Synthetic Hybrid Data-Reference-Cited by-同舟云学术

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Weakly-Supervised Scene-Specific Crowd Counting Using Real-Synthetic Hybrid Data

Published:2023-06-04 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Fan Yaowu¹,Wan Jia²,Yuan Yuan³,Wang Qi³

Affiliation:

1. Northwestern Polytechnical University,School of Software,Xi’an,Shaanxi,P. R. China,710072

2. University of California,Department of Electrical and Computer Engineering,San Diego,USA

3. Northwestern Polytechnical University,School of Artificial Intelligence, OPtics and ElectroNics (iOPEN),Xi’an,Shaanxi,P. R. China,710072

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10094559/10094560/10095275.pdf?arnumber=10095275

Reference21 articles.

1. Enhancing and Dissecting Crowd Counting by Synthetic Data

2. Learning From Synthetic Data for Crowd Counting in the Wild

3. How Realistic Should Synthetic Images Be for Training Crowd Counting Models?

4. Leveraging Self-Supervision for Cross-Domain Crowd Counting

5. Distribution matching for crowd counting;wang;Advances in neural information processing systems,2020

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