Yujiang Li1,2, Chun Ding1,2, Zhili Zhou1,2,*
Journal of New Media, Vol.4, No.1, pp. 51-58, 2022, DOI:10.32604/jnm.2022.028775
Abstract With the development of new media technology, vehicle matching plays a further significant role in video surveillance systems. Recent methods explored the vehicle matching based on the feature extraction. Meanwhile, similarity metric learning also has achieved enormous progress in vehicle matching. But most of these methods are less effective in some realistic scenarios where vehicles usually be captured in different times. To address this cross-domain problem, we propose a cross-domain similarity metric learning method that utilizes the GAN to generate vehicle images with another domain and propose the two-channel Siamese network to learn a similarity metric from both domains (i.e.,… More >
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