588 citations · 632 across the 12 of their papers we have counts for
4 papers · 1 filter
Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach
Behnam Gholami, Pritish Sahu, Ognjen Rudovic +2
Unsupervised domain adaptation (uDA) models focus on pairwise adaptation settings where there is a single, labeled, source and a single target domain. However, in many real-world s…
XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings
Amélie Royer, Konstantinos Bousmalis, Stephan Gouws +4
Style transfer usually refers to the task of applying color and texture information from a specific style image to a given content image while preserving the structure of the latte…
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
Konstantinos Bousmalis, Nathan Silberman, David Dohan +2
Collecting well-annotated image datasets to train modern machine learning algorithms is prohibitively expensive for many tasks. One appealing alternative is rendering synthetic dat…
Domain Separation Networks
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman +2
The cost of large scale data collection and annotation often makes the application of machine learning algorithms to new tasks or datasets prohibitively expensive. One approach cir…