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Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping
Unsupervised domain mapping aims to learn a function G(XY) to translate domain [Formula: see text] to [Formula: see text] in the absence of paired examples. Finding the optimal G(XY) without paired data is an ill-posed problem, so appropriate constraints are required to obtain reasonable solutions....
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| Publicado en: | Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
2020
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7030214/ https://ncbi.nlm.nih.gov/pubmed/32076365 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/cvpr.2019.00253 |
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