DRIT++: Diverse Image-to-Image Translation via Disentangled Representations

Image-to-image translation aims to learn the mapping between two visual domains. There are two main challenges for this task: (1) lack of aligned training pairs and (2) multiple possible outputs from a single input image. In this work, we present an approach based on disentangled representation for...

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Bibliographische Detailangaben

Veröffentlicht in:	International journal of computer vision Jg. 128; H. 10-11; S. 2402 - 2417
Hauptverfasser:	Lee, Hsin-Ying, Tseng, Hung-Yu, Mao, Qi, Huang, Jia-Bin, Lu, Yu-Ding, Singh, Maneesh, Yang, Ming-Hsuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.11.2020 Springer
Schlagworte:	Artificial Intelligence Computer Imaging Computer Science Image Processing and Computer Vision Pattern Recognition Pattern Recognition and Graphics Special Issue on Generative Adversarial Networks for Computer Vision Vision
ISSN:	0920-5691, 1573-1405
Online-Zugang:	Volltext
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