RCAA: relational context-aware agents for person search

Xiaojun Chang, Po-Yao Huang, Yi-Dong Shen, Xiaodan Liang, Yi Yang, Alexander G. Hauptmann

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

27 Citations (Scopus)


We aim to search for a target person from a gallery of whole scene images for which the annotations of pedestrian bounding boxes are unavailable. Previous approaches to this problem have relied on a pedestrian proposal net, which may generate redundant proposals and increase the computational burden. In this paper, we address this problem by training relational context-aware agents which learn the actions to localize the target person from the gallery of whole scene images. We incorporate the relational spatial and temporal contexts into the framework. Specifically, we propose to use the target person as the query in the query-dependent relational network. The agent determines the best action to take at each time step by simultaneously considering the local visual information, the relational and temporal contexts, together with the target person. To validate the performance of our approach, we conduct extensive experiments on the large-scale Person Search benchmark dataset and achieve significant improvements over the compared approaches. It is also worth noting that the proposed model even performs better than traditional methods with perfect pedestrian detectors.

Original languageEnglish
Title of host publicationComputer Vision – ECCV 2018
Subtitle of host publication15th European Conference Munich, Germany, September 8–14, 2018 Proceedings, Part IX
EditorsVittorio Ferrari, Martial Hebert, Cristian Sminchisescu, Yair Weiss
Place of PublicationCham Switzerland
Number of pages17
ISBN (Electronic)9783030012403
ISBN (Print)9783030012397
Publication statusPublished - 2018
Externally publishedYes
EventEuropean Conference on Computer Vision 2018 - Munich, Germany
Duration: 8 Sept 201814 Sept 2018
Conference number: 15th
https://link.springer.com/book/10.1007/978-3-030-01246-5 (Proceedings)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceEuropean Conference on Computer Vision 2018
Abbreviated titleECCV 2018
Internet address


  • Person search
  • Relational network

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