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SketchDesc: Learning Local Sketch Descriptors for Multi-view Correspondence

Yu, Deng, Li, Lei, Zheng, Youyi, Lau, Manfred, Song, Yi-Zhe, Tai, Chiew-Lan and Fu, Hongbo (2020) SketchDesc: Learning Local Sketch Descriptors for Multi-view Correspondence IEEE Transactions on Circuits and Systems for Video Technology.

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Abstract

In this paper, we study the problem of multi-view sketch correspondence, where we take as input multiple freehand sketches with different views of the same object and predict as output the semantic correspondence among the sketches. This problem is challenging since the visual features of corresponding points at different views can be very different. To this end, we take a deep learning approach and learn a novel local sketch descriptor from data. We contribute a training dataset by generating the pixel-level correspondence for the multi-view line drawings synthesized from 3D shapes. To handle the sparsity and ambiguity of sketches, we design a novel multi-branch neural network that integrates a patch-based representation and a multiscale strategy to learn the pixel-level correspondence among multi-view sketches. We demonstrate the effectiveness of our proposed approach with extensive experiments on hand-drawn sketches and multi-view line drawings rendered from multiple 3D shape datasets.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Yu, Deng
Li, Lei
Zheng, Youyi
Lau, Manfred
Song, Yi-Zhey.song@surrey.ac.uk
Tai, Chiew-Lan
Fu, Hongbo
Date : 10 August 2020
DOI : 10.1109/TCSVT.2020.3015279
Copyright Disclaimer : © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Multi-view sketches; Correspondence learning; Multi-scale; Patch-based descriptor
Depositing User : Diane Maxfield
Date Deposited : 07 Oct 2020 16:42
Last Modified : 07 Oct 2020 16:42
URI: http://epubs.surrey.ac.uk/id/eprint/858712

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