Fine-Grained Color Sketch-Based Image Retrieval

Yu Xia, Shuangbu Wang, Yanran Li, Lihua You, Xiaosong Yang, Jian Jun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We propose a novel fine-grained color sketch-based image retrieval (CSBIR) approach. The CSBIR problem is investigated for the first time using deep learning networks, in which deep features are used to represent color sketches and images. A novel ranking method considering both shape matching and color matching is also proposed. In addition, we build a CSBIR dataset with color sketches and images to train and test our method. The results show that our method has better retrieval performance.
Original languageEnglish
Title of host publicationAdvances in Computer Graphics: 36th Computer Graphics International Conference, CGI 2019, Calgary, AB, Canada, June 17–20, 2019, Proceedings
EditorsMarina Gavrilova, Jian Chang, Nadia Magnenat Thalmann, Eckhard Hitzer, Hiroshi Ishikawa
Place of PublicationCham
PublisherSpringer, Cham
Number of pages7
ISBN (Electronic)978-3-030-22514-8
ISBN (Print)978-3-030-22513-1
Publication statusPublished - 12 Jun 2019
EventComputer Graphics International 2019 - Calgary, Canada
Duration: 17 Jun 201920 Jun 2019
Conference number: 36

Publication series

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


ConferenceComputer Graphics International 2019
Abbreviated titleCGI 2019
Internet address

Keywords / Materials (for Non-textual outputs)

  • Color sketch
  • Image retrieval
  • Deep learning
  • Triplet network


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