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AA-RGTCN: reciprocal global temporal convolution network with adaptive alignment for video-based person re-identification. [PDF]

Front Neurosci
Zhang Y, Lin Y, Yang X.
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Isosceles Constraints for Person Re-Identification

IEEE Transactions on Image Processing, 2020
In the existing works of person re-identification (ReID), batch hard triplet loss has achieved great success. However, it only cares about the hardest samples within the batch. For any probe, there are massive mismatched samples (crucial samples) outside the batch which are closer than the matched samples.
Furong Xu, Bingpeng Ma, Hong Chang 0001, Shiguang Shan   +3 more
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Partial Person Re-Identification

2015 IEEE International Conference on Computer Vision (ICCV), 2015
We address a new partial person re-identification (re-id) problem, where only a partial observation of a person is available for matching across different non-overlapping camera views. This differs significantly from the conventional person re-id setting where it is assumed that the full body of a person is detected and aligned.
Wei-Shi Zheng 0001, Xiang Li 0032, Tao Xiang 0002, Shengcai Liao, Jian-Huang Lai, Shaogang Gong   +5 more
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Complementary networks for person re-identification

Information Sciences, 2023
This study is supported under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative (No. NTU 2018-0551), as well as cash and in-kind contribution from Singapore Telecommunications Limited (Singtel), through Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU).
Zhang, Guoqing, Lin, Weisi, Chandran, Arun Kumar, Jing, Xuan   +3 more
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Person in Uniforms Re-Identification

ACM Transactions on Multimedia Computing, Communications, and Applications
Person in Uniforms Re-identification (PU-ReID) is an emerging computer vision task for various intelligent video surveillance applications. PU-ReID is much understudied due to the absence of large-scale annotated datasets, also this task is extremely challenging because many individuals captured in surveillance videos wear same clothing, introducing ...
Chong-Yang Xiang, Xiao Wu 0001, Jun-Yan He, Zhaoquan Yuan, Tingquan He   +4 more
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Face in Person Re-Identification

2014
The face represents one of the most diffused and established biometrics for both identity verification and recognition with a large corpus of research focused on advancing the accuracy, the robustness, and the response speed of face recognition systems by means of 2D, 3D, and hybrid approaches.
Abate, Andrea F., RICCIARDI, STEFANO, Tortora, Genoveffa   +2 more
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Bidirectional ranking for person re-identification

2013 IEEE International Conference on Multimedia and Expo (ICME), 2013
This paper proposes a simple but efficient bidirectional ranking method to improve person re-identification results across non-overlapping cameras. Previous methods treat person reidentification as a special object retrieval problem, and compute the final rank result purely based on a unidirectional matching between the probe and all gallery images ...
Qingming Leng, Ruimin Hu, Chao Liang 0001, Yimin Wang, Jun Chen 0001   +4 more
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Person Re-identification by Salience Matching

2013 IEEE International Conference on Computer Vision, 2013
Human salience is distinctive and reliable information in matching pedestrians across disjoint camera views. In this paper, we exploit the pair wise salience distribution relationship between pedestrian images, and solve the person re-identification problem by proposing a salience matching strategy.
Rui Zhao 0001, Wanli Ouyang, Xiaogang Wang 0001   +2 more
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Person Re-identification Based on Hash

2021
Person re-identificaton aims to retrieve interested person objects from the person image database in cross camera scene, which has a wide range of application value in the field of video surveillance and security. With the generation of massive monitoring data, the retrieval speed of person re-identificaton is required to be higher.
Bo Song, Xinfeng Zhang 0002, Tianyu Zhu, Bowen Ren, Maoshen Jia   +4 more
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An improved baseline for person re-identification

Proceedings of the 2nd International Conference on Artificial Intelligence and Pattern Recognition, 2019
Person re-identification(Re-ID) using deep learning has made great progress in the past few years, but there is one problem that many state-of-the-art Re-ID methods all use a complex network most of which use the structure of multi-branch and multi-loss function. At present, the database used for Person re-identification is relatively small.
Yu Liu, Youdong Ding
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