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Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
[article]
2018
arXiv
pre-print
Employing part-level features for pedestrian image description offers fine-grained information and has been verified as beneficial for person retrieval in very recent literature. A prerequisite of part discovery is that each part should be well located. Instead of using external cues, e.g., pose estimation, to directly locate parts, this paper lays emphasis on the content consistency within each part. Specifically, we target at learning discriminative part-informed features for person retrieval
arXiv:1711.09349v3
fatcat:wmcahe2w5zdnvcambuhuskidyq