2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDARS-4.1
Paper Title HIGH CONFIDENCE ATTRIBUTE RECOGNITION FOR VEHICLE RE-IDENTIFICATION
Authors Xinze Dou, Yang Liu, Kai Lv, Zhang Xiong, Hao Sheng, Beihang University, China
SessionARS-4: Re-Identification and Retrieval
LocationArea I
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Image and Video Analysis, Synthesis, and Retrieval: Image & Video Storage and Retrieval
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Vehicle re-identification aims to associate images or videos of the same vehicle collected from different cameras. Many existing methods address the vehicle re-identification problem by explicitly learning distinguishable global features. However, vehicle attributes, i.e., logo category and orientation, play an indispensable role in identifying vehicles. In this paper, we first propose deep models to recognize vehicle attributes. Then, based on these attributes, we adopt a High Confidence Attribute Network (HCANet) to extract weighted global features. A comprehensive evaluation on the VehicleID dataset shows that our approach achieves competitive results.