Home | << 1 >> |
Record | |||||
---|---|---|---|---|---|
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 | ||
Keywords | |||||
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 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ACM-MM | ||
Notes | LAMP; 600.106; 600.109; 600.141; 600.120 | Approved | no | ||
Call Number | Admin @ si @ WGW2019 | Serial | 3363 | ||
Permanent link to this record |