期刊论文

Liu, SB

英文

Journal of Visual Communication and Image Representation

1047-3203

2023

97

103972

10.1016/j.jvcir.2023.103972

Fig. 1 illustrates the overall architecture of the BFB-PTT method, which consists of a backbone network and a Bidirectional Fusion Branch (BFB), with sample space optimization through the PTT loss function. The BFB incorporates a short path fusion of low-level and high-level features, which gives it an advantage over traditional methods in terms of extracting and preserving low-level features. As shown in the diagram, the BFB connects various layers of ResNet50. The feature maps learned from

本校为第一且通讯机构

Person re-identification (Re-ID) is the recognition of the same person in different camera views. Because of the existence of highly similar persons and great differences of the same person in different scenes, and the fact that the features extracted by current mainstream models lose some fine-grained information, it is likely for the models to misidentify the query person. To tackle these challenges, we introduce a bidirectional fusion branch network with penalty term-based trihard loss (BFB-PTT). The BFB-PTT constructs a bidirectional fusion...