Abstract
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.
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Acknowledgements
This research is supported by the PDE-GIR project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 778035. Yanran Li has received research grands from the South West Creative Technology Network.
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Xia, Y., Wang, S., Li, Y., You, L., Yang, X., Zhang, J.J. (2019). Fine-Grained Color Sketch-Based Image Retrieval. In: Gavrilova, M., Chang, J., Thalmann, N., Hitzer, E., Ishikawa, H. (eds) Advances in Computer Graphics. CGI 2019. Lecture Notes in Computer Science(), vol 11542. Springer, Cham. https://doi.org/10.1007/978-3-030-22514-8_40
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DOI: https://doi.org/10.1007/978-3-030-22514-8_40
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