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Author  |
Yaxing Wang; Abel Gonzalez-Garcia; Joost Van de Weijer; Luis Herranz |
 
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| Title | SDIT: Scalable and Diverse Cross-domain Image Translation | Type | Conference Article | |||
| Year | 2019 | Publication | 27th ACM International Conference on Multimedia | Abbreviated Journal | ||
| Volume | Issue | Pages | 1267–1276 | |||
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| Abstract | Recently, image-to-image translation research has witnessed remarkable progress. Although current approaches successfully generate diverse outputs or perform scalable image transfer, these properties have not been combined into a single method. To address this limitation, we propose SDIT: Scalable and Diverse image-to-image translation. These properties are combined into a single generator. The diversity is determined by a latent variable which is randomly sampled from a normal distribution. The scalability is obtained by conditioning the network on the domain attributes. Additionally, we also exploit an attention mechanism that permits the generator to focus on the domain-specific attribute. We empirically demonstrate the performance of the proposed method on face mapping and other datasets beyond faces. | |||||
| Address | Nice; Francia; October 2019 | |||||
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| Area | Expedition | Conference | ACM-MM | |||
| Notes | LAMP; 600.106; 600.109; 600.141; 600.120;CIC | Approved | no | |||
| Call Number | Admin @ si @ WGW2019 | Serial | 3363 | |||
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