Attribute-Driven Spontaneous Motion in Unpaired Image Translation

被引：10
|
作者：
Wu, Ruizheng [1 ]
Tao, Xin [2 ]
Gu, Xiaodong [3 ]
Shen, Xiaoyong [2 ]
Jia, Jiaya [1 ,2 ]
机构：
[1] Chinese Univ Hong Kong, Hong Kong, Peoples R China
[2] Tencent YouTu Lab, Shenzhen, Peoples R China
[3] Harbin Inst Technol, Shenzhen, Peoples R China
来源：
2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019) | 2019年
关键词：
D O I：
10.1109/ICCV.2019.00602
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Current image translation methods, albeit effective to produce high-quality results in various applications, still do not consider much geometric transform. We in this paper propose the spontaneous motion estimation module, along with a refinement part, to learn attribute-driven deformation between source and target domains. Extensive experiments and visualization demonstrate effectiveness of these modules. We achieve promising results in unpaired-image translation tasks, and enable interesting applications based on spontaneous motion.
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页码：5922 / 5931
页数：10
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