CLDE-Net: crowd localization and density estimation based on CNN and transformer network-Reference-Cited by-同舟云学术

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CLDE-Net: crowd localization and density estimation based on CNN and transformer network

Published:2024-04-08 Issue:3 Volume:30 Page:
ISSN:0942-4962
Container-title:Multimedia Systems
language:en
Short-container-title:Multimedia Systems

Author:

Hu Yaocong,Lin Yuanyuan,Yang Huicheng,Liu Bingyou,Wan Guoyang,Hong Jinwen,Xie Chao,Wang Wei,Lu Xiaobo

Funder

National Natural Science Foundation of China

Natural Science Foundation of the Anhui Higher Education Institutions of China

Open Research Fund of AnHui Key Laboratory of Detection Technology and Energy Saving Devices

Anhui Polytechnic University of Technology Introduced Talent Research Startup Fund

Youth Foundation of Anhui Polytechnic University

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00530-024-01318-8.pdf

Reference71 articles.

1. Abousamra, S., Hoai, M., Samaras, D., Chen, C.: Localization in the crowd with topological constraints. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 872–881 (2021)

2. Babu Sam, D., Surya, S., Venkatesh Babu, R.: Switching convolutional neural network for crowd counting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5744–5752 (2017)

3. Basalamah, S., Khan, S.D., Ullah, H.: Scale driven convolutional neural network model for people counting and localization in crowd scenes. IEEE Access 7, 71576–71584 (2019). https://doi.org/10.1109/ACCESS.2019.2918650

4. Boominathan, L., Kruthiventi, S.S., Babu, R.V.: Crowdnet: a deep convolutional network for dense crowd counting. In: Proceedings of the 24th ACM International Conference on Multimedia, pp. 640–644 (2016)

5. Cao, J., Pang, Y., Xie, J., Khan, F.S., Shao, L.: From handcrafted to deep features for pedestrian detection: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(9), 4913–4934 (2022). https://doi.org/10.1109/TPAMI.2021.3076733

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