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| Author | Yaxing Wang; Abel Gonzalez-Garcia; Joost Van de Weijer; Luis Herranz | ||||
| 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 | Approved | no | ||
| Call Number | Admin @ si @ WGW2019 | Serial | 3363 | ||
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