The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Multi-scale Deep Learning Architectures for Person Re-identification
Open accessAbstract
Person Re-identification (re-id) aims to match people across non-overlapping camera views in a public space. It is a challenging problem because many people captured in surveillance videos wear similar clothes. Consequently, the differences in their appearance are often subtle and only detectable at the right location and scales. Existing re-id models, particularly the recently proposed deep learning based ones match people at a single scale. In contrast, in this paper, a novel multi-scale deep learning model is proposed. Our model is able to learn deep discriminative feature representations at different scales and automatically determine the most suitable scales for matching. The importance of different spatial locations for extracting discriminative features is also learned explicitly. Experiments are carried out to demonstrate that the proposed model outperforms the state-of-the art on a number of benchmarks.
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Cited by
Harmonious Attention Network for Person Re-identification
Li, W., Zhu, X., & Gong, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00243 · Cited by 1,449
Resource Aware Person Re-identification Across Multiple Resolutions
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Deep-Person: Learning discriminative deep features for person Re-Identification
Bai, X., Yang, M., Huang, T., Dou, Z., Yu, R., & Xu, Y. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2019.107036 · Cited by 266
A comprehensive review of recent advances on deep vision systems
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Lei, H., Liu, S., Elazab, A., Gong, X., & Lei, B. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.3027566 · Cited by 46
Metadata
- Authors
- Qian, X., Fu, Y., Jiang, Y.-G., Xiang, T., & Xue, X.
- Venue
- 2017 IEEE International Conference on Computer Vision (ICCV)
- Publisher
- IEEE
- Published
- 2017-10
- Pages
- 5409-5418
- OpenAlex
- W2963690547
- Cited by
- 319
- References
- 58
- FWCI
- 11.16
- Type
- conference paper
- Language
- en
- Open access
- green
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