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Fine-Grained Color Sketch-Based Image Retrieval.

Xia, Y., Wang, S., Li, Y., You, L., Yang, X. and Zhang, J. J., 2019. Fine-Grained Color Sketch-Based Image Retrieval. In: CGI 2019: Advances in Computer Graphics, 17-20 June 2019, Calgary, AB, Canada, 424 - 430.

Full text available as:

CGI_2019_paper_253.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.


DOI: 10.1007/978-3-030-22514-8_40


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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Color sketch; Image retrieval; Deep learning; Triplet network
Group:Faculty of Media & Communication
ID Code:32502
Deposited By: Symplectic RT2
Deposited On:09 Jul 2019 07:43
Last Modified:14 Mar 2022 14:16


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