How Realistic Should Synthetic Images Be for Training Crowd Counting Models?-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

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

Published:2021 Issue: Volume: Page:46-56
ISSN:0302-9743
Container-title:Computer Analysis of Images and Patterns
language:
Short-container-title:

Author:

Ledda Emanuele,Putzu Lorenzo^ORCID,Delussu Rita^ORCID,Loddo Andrea^ORCID,Fumera Giorgio^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-89131-2_5

Reference27 articles.

1. Cao, Z., Shamsolmoali, P., Yang, J.: Synthetic guided domain adaptive and edge aware network for crowd counting. Image Vis. Comput. 104, 104026 (2020)

2. Chan, A.B., Liang, Z.S.J., Vasconcelos, N.: Privacy preserving crowd monitoring: counting people without people models or tracking. In: CVPR, pp. 1–7 (2008)

3. Chen, K., Loy, C.C., Gong, S., Xiang, T.: Feature mining for localised crowd counting. In: BMVC, pp. 1–11 (2012)

4. Chen, Y., Zhu, X., Gong, S.: Instance-guided context rendering for cross-domain person re-identification. In: ICCV, pp. 232–242 (2019)

5. Delussu, R., Putzu, L., Fumera, G.: Investigating synthetic data sets for crowd counting in cross-scene scenarios. In: VISIGRAPP, pp. 365–372 (2020)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Synthetic Data for Video Surveillance Applications of Computer Vision: A Review;International Journal of Computer Vision;2024-05-17

2. Weakly-Supervised Scene-Specific Crowd Counting Using Real-Synthetic Hybrid Data;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3