PARTITION AND REUNION: A VIEWPOINT-AWARE LOSS FOR VEHICLE RE-IDENTIFICATION

Haobo Chen, Yang Liu, Yang Huang, Wei Ke, Hao Sheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Vehicle Re-Identification (ReID) aims to retrieve images of vehicles with the same identity from different scenarios. It is a challenging task due to the large intra-identity discrepancy caused by viewpoint variations and the subtle inter-identity difference produced by similar appearances. In this paper, we propose a Viewpoint-Aware Loss (VAL) function to deal with these challenges. Specifically, we propose partition and reunion operations in VAL, which significantly shrinks the intra-identity distance and acquires viewpoint-invariant representations. In addition, we embed a multi-decision boundary mechanism in VAL. It contributes to enlarging the inter-identity distance. A comprehensive evaluation on two benchmarks shows the superiority of our method in contrast to a series of existing state-of-the-arts.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Image Processing, ICIP 2022 - Proceedings
PublisherIEEE Computer Society
Pages2246-2250
Number of pages5
ISBN (Electronic)9781665496209
DOIs
Publication statusPublished - 2022
Event29th IEEE International Conference on Image Processing, ICIP 2022 - Bordeaux, France
Duration: 16 Oct 202219 Oct 2022

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference29th IEEE International Conference on Image Processing, ICIP 2022
Country/TerritoryFrance
CityBordeaux
Period16/10/2219/10/22

Keywords

  • Vehicle re-identification
  • loss function
  • representation learning
  • viewpoint-aware

Fingerprint

Dive into the research topics of 'PARTITION AND REUNION: A VIEWPOINT-AWARE LOSS FOR VEHICLE RE-IDENTIFICATION'. Together they form a unique fingerprint.

Cite this