Abstract
We present a method for recovering the shared content between two visual domains as well as the content that is unique to each domain. This allows us to map from one domain to the other, in a way in which the content that is specific for the first domain is removed and the content that is specific for the second is imported from any image in the second domain. In addition, our method enables generation of images from the intersection of the two domains as well as their union, despite having no such samples during training. The method is shown analytically to contain all the sufficient and necessary constraints. It also outperforms the literature methods in an extensive set of experiments.
Original language | English |
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Title of host publication | Proceedings - 2019 International Conference on Computer Vision, ICCV 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 3444-3452 |
Number of pages | 9 |
ISBN (Electronic) | 9781728148038 |
DOIs | |
State | Published - Oct 2019 |
Externally published | Yes |
Event | 17th IEEE/CVF International Conference on Computer Vision, ICCV 2019 - Seoul, Korea, Republic of Duration: 27 Oct 2019 → 2 Nov 2019 |
Publication series
Name | Proceedings of the IEEE International Conference on Computer Vision |
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ISSN (Print) | 1550-5499 |
Conference
Conference | 17th IEEE/CVF International Conference on Computer Vision, ICCV 2019 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 27/10/19 → 2/11/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.