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Short Range Correlation Transformer for Occluded Person Re-Identification. (arXiv:2201.01090v1 [cs.CV])
Jan. 5, 2022, 2:10 a.m. | Yunbin Zhao, Songhao Zhu, Dongsheng Wang, Zhiwei Liang
cs.CV updates on arXiv.org arxiv.org
Occluded person re-identification is one of the challenging areas of computer
vision, which faces problems such as inefficient feature representation and low
recognition accuracy. Convolutional neural network pays more attention to the
extraction of local features, therefore it is difficult to extract features of
occluded pedestrians and the effect is not so satisfied. Recently, vision
transformer is introduced into the field of re-identification and achieves the
most advanced results by constructing the relationship of global features
between patch sequences. However, …
More from arxiv.org / cs.CV updates on arXiv.org
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