An anchor-free object detector based on soften optimized bi-directional FPN-Reference-Cited by-同舟云学术

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An anchor-free object detector based on soften optimized bi-directional FPN

Published:2022-04 Issue: Volume:218 Page:103410
ISSN:1077-3142
Container-title:Computer Vision and Image Understanding
language:en
Short-container-title:Computer Vision and Image Understanding

Author:

Zhang Tao^ORCID,Jin Bo^ORCID,Jia Wenjing

Funder

Nanjing University of Information Science and Technology

Key Laboratory of Image and Video Understanding for Social Safety

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Nanjing University of Science and Technology

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference61 articles.

1. YOLOv4: Optimal speed and accuracy of object detection;Bochkovskiy,2020

2. Bodla, N., Singh, B., Chellappa, R., Davis, L.S., 2017. Soft-NMS–improving object detection with one line of code. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 5561–5569.

3. Cai, Z., Vasconcelos, N., 2018. Cascade r-cnn: Delving into high quality object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 6154–6162.

4. Cao, Z., Simon, T., Wei, S.-E., Sheikh, Y., 2017. Realtime multi-person 2d pose estimation using part affinity fields. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 7291–7299.

5. Carreira, J., Zisserman, A., 2017. Quo vadis, action recognition? a new model and the kinetics dataset. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 6299–6308.

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