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Enhancing Sketch-Based Image Retrieval via Deep Discriminative Representation
Fei Huang, Yong Cheng, Cheng Jin, Yuejie Zhang, Tao Zhang
1626 - 1627
10.3233/978-1-61499-672-9-1626
Frontiers in Artificial Intelligence and Applications
Volume 285: ECAI 2016
Abstract

In this paper we aim to employ deep learning to enhance SBIR via deep discriminative representation. Our main contributions focus on: 1) The deep discriminative representation is established to bridge both the visual appearance gap and the semantic gap between sketches and images; 2) The deep learning pattern is applied to our SBIR model through training on our transformed sketch-like images to overcome the rarity of training sketches. Our experiments on a large number of public sketch and image data have obtained very positive results.

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