Projects per year
Abstract
Unsupervised image-to-image translation techniques are able to map local texture between two domains, but they are typically unsuccessful when the domains require larger shape change. Inspired by semantic segmentation, we introduce a discriminator with dilated convolutions that is able to use information from across the entire image to train a more context-aware generator. This is coupled with a multi-scale perceptual loss that is better able to represent error in the underlying shape of objects. We demonstrate that this design is more capable of representing shape deformation in a challenging toy dataset, plus in complex mappings with significant dataset variation between humans, dolls, and anime faces, and between cats and dogs.
Original language | English |
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Title of host publication | Proceedings of European Conference on Computer Vision (ECCV) |
Subtitle of host publication | Computer Vision - ECCV 2018 |
Editors | Vittorio Ferrari, Martial Hebert, Cristian Sminchisescu, Yair Weiss |
Publisher | Springer Verlag |
Pages | 662-678 |
Number of pages | 17 |
Volume | 11216 |
ISBN (Electronic) | 978-3-030-01258-8 |
ISBN (Print) | 978-3-030-01257-1 |
DOIs | |
Publication status | E-pub ahead of print - 6 Oct 2018 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11216 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Keywords
- Generative adversarial networks
- Image translation
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
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Projects
- 1 Finished
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Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)
Cosker, D., Campbell, N., Fincham Haines, T., Hall, P., Kim, K. I., Lutteroth, C., O'Neill, E., Richardt, C. & Yang, Y.
Engineering and Physical Sciences Research Council
1/09/15 → 28/02/21
Project: Research council