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pro vyhledávání: '"Liu, Xuehu"'
Large-scale language-image pre-trained models (e.g., CLIP) have shown superior performances on many cross-modal retrieval tasks. However, the problem of transferring the knowledge learned from such models to video-based person re-identification (ReID
Externí odkaz:
http://arxiv.org/abs/2312.09627
Multi-spectral object Re-identification (ReID) aims to retrieve specific objects by leveraging complementary information from different image spectra. It delivers great advantages over traditional single-spectral ReID in complex visual environment. H
Externí odkaz:
http://arxiv.org/abs/2312.09612
Video-based person Re-Identification (V-ReID) aims to retrieve specific persons from raw videos captured by non-overlapped cameras. As a fundamental task, it spreads many multimedia and computer vision applications. However, due to the variations of
Externí odkaz:
http://arxiv.org/abs/2308.03703
Advanced deep Convolutional Neural Networks (CNNs) have shown great success in video-based person Re-Identification (Re-ID). However, they usually focus on the most obvious regions of persons with a limited global representation ability. Recently, it
Externí odkaz:
http://arxiv.org/abs/2304.14122
Autor:
Liu, Xuehui
Publikováno v:
Dissertations and Theses.
The herpes simplex virus 1 (HSVl) VP5 gene codes for the major viral capsid protein. Understanding of the mechanism of how the VP5 gene is regulated in host cells will help us to understand the molecular action of the HSV 1 life cycle and its interpl
Video-based person re-identification (Re-ID) aims to retrieve video sequences of the same person under non-overlapping cameras. Previous methods usually focus on limited views, such as spatial, temporal or spatial-temporal view, which lack of the obs
Externí odkaz:
http://arxiv.org/abs/2104.01745
Video-based person re-identification (Re-ID) aims to automatically retrieve video sequences of the same person under non-overlapping cameras. To achieve this goal, it is the key to fully utilize abundant spatial and temporal cues in videos. Existing
Externí odkaz:
http://arxiv.org/abs/2103.04337
Autor:
Liu, Xuehu, Liu, Min, Dong, Huiyu, Zhang, Dandan, Du, Hanchun, Goodman, Bernard A., Liu, Shaogang, Diao, Kaisheng
Publikováno v:
In Journal of Water Process Engineering June 2022 47
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