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王建元 博士后:Parallelly conquer the large variance of person re-identification

本站小编 Free考研考试/2021-12-26



Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker: 王建元 博士后,北京航空航天大学
Inviter:
Title:
Parallelly conquer the large variance of person re-identification
Time & Venue:
2021.11.27 09:00-10:00 腾讯会议ID: 342420406
Abstract:
Person re-identification has a wide range of applications, and many state-of-the-art methods are proposed to solve the problem under specific scenarios. However, it is still a challenging issue because of the large variance in practical applications, such as pose variations, misalignment, and image noises. Parallelly Conquer Net (PCNet) is proposed to deal with large variance in a parallel manner. PCNet consists of three module: Pose Adaptation Module (PAM), Global Alignment Module (GAM), and Pixel-Wised Attention Module (PWAM). Each module is designed to deal with a sub-variance independently. Furthermore, the generated features are aggregated by parallel branches to utilize complementary information among them.

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