Deep Self-Supervised Representation Learning for Free-Hand Sketch

doi:10.1109/TCSVT.2020.3003048

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能感知与计算研究中心

	Deep Self-Supervised Representation Learning for Free-Hand Sketch
	Xu, Peng 1; Song, Zeyu 4; Yin, Qiyue 3; Song, Yi-Zhe 2; Wang, Liang 3
刊名	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
	2021-04-01
卷号	31 期号:4 页码:1503-1513
关键词	Feature extraction Task analysis Strain Computer architecture Deep learning Deformable models Convolution Self-supervised representation learning deep learning sketch pretext task textual convolution network convolutional neural network
ISSN号	1051-8215
DOI	10.1109/TCSVT.2020.3003048
通讯作者	Xu, Peng(peng.xu@ntu.edu.sg)
英文摘要	In this paper, we tackle for the first time, the problem of self-supervised representation learning for free-hand sketches. This importantly addresses a common problem faced by the sketch community - that annotated supervisory data are difficult to obtain. This problem is very challenging in which sketches are highly abstract and subject to different drawing styles, making existing solutions tailored for photos unsuitable. Key for the success of our self-supervised learning paradigm lies with our sketch-specific designs: (i) we propose a set of pretext tasks specifically designed for sketches that mimic different drawing styles, and (ii) we further exploit the use of the textual convolution network (TCN) together with the convolutional neural network (CNN) in a dual-branch architecture for sketch feature learning, as means to accommodate the sequential stroke nature of sketches. We demonstrate the superiority of our sketch-specific designs through two sketch-related applications (retrieval and recognition) on a million-scale sketch dataset, and show that the proposed approach outperforms the state-of-the-art unsupervised representation learning methods, and significantly narrows the performance gap between with supervised representation learning. (1) (1) PyTorch code of this work is available at https://github.com/zzz1515151/self-supervised_learning_sketch.
资助项目	BUPT Excellent Ph.D. ; Student Foundation[CX2017307] ; BUPT-SICE Excellent Graduate Student Innovation Foundation
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000637537200021
资助机构	BUPT Excellent Ph.D. ; Student Foundation ; BUPT-SICE Excellent Graduate Student Innovation Foundation
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/44248]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Xu, Peng
作者单位	1.Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore 2.Univ Surrey, Ctr Vis Speech & Signal Proc, Guildford GU2 7XH, Surrey, England 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China
推荐引用方式 GB/T 7714	Xu, Peng,Song, Zeyu,Yin, Qiyue,et al. Deep Self-Supervised Representation Learning for Free-Hand Sketch[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2021,31(4):1503-1513.
APA	Xu, Peng,Song, Zeyu,Yin, Qiyue,Song, Yi-Zhe,&Wang, Liang.(2021).Deep Self-Supervised Representation Learning for Free-Hand Sketch.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,31(4),1503-1513.
MLA	Xu, Peng,et al."Deep Self-Supervised Representation Learning for Free-Hand Sketch".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 31.4(2021):1503-1513.