1 code implementation • 15 Dec 2023 • Shang Gao, Chenyang Yu, Pingping Zhang, Huchuan Lu
In addition, existing occluded person ReID benchmarks utilize occluded samples as queries, which will amplify the role of alleviating occlusion interference and underestimate the impact of the feature absence issue.
1 code implementation • 15 Dec 2023 • Chenyang Yu, Xuehu Liu, Yingquan Wang, Pingping Zhang, Huchuan Lu
Technically, TMC allows the frame-level memories in a sequence to communicate with each other, and to extract temporal information based on the relations within the sequence.
1 code implementation • 27 Apr 2023 • Xuehu Liu, Chenyang Yu, Pingping Zhang, Huchuan Lu
Further, in spatial, we propose a Complementary Content Attention (CCA) to take advantages of the coupled structure and guide independent features for spatial complementary learning.
no code implementations • 3 Dec 2021 • Lianjie Jia, Chenyang Yu, Xiehao Ye, Tianyu Yan, Yinjie Lei, Pingping Zhang
To generate high-quality pseudo-labels and mitigate the impact of clustering errors, we propose a novel clustering relationship modeling framework for unsupervised person Re-ID.
no code implementations • 5 Apr 2021 • Xuehu Liu, Pingping Zhang, Chenyang Yu, Huchuan Lu, Xuesheng Qian, Xiaoyun Yang
To capture richer perceptions and extract more comprehensive video representations, in this paper we propose a novel framework named Trigeminal Transformers (TMT) for video-based person Re-ID.
1 code implementation • CVPR 2021 • Xuehu Liu, Pingping Zhang, Chenyang Yu, Huchuan Lu, Xiaoyun Yang
Specifically, we first propose a Global-guided Correlation Estimation (GCE) to generate feature correlation maps of local features and global features, which help to localize the high- and low-correlation regions for identifying the same person.