Search Results for author:
Found 3 papers, 1 papers with code
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
In this work, we connect two distinct concepts for unsupervised domain adaptation: feature distribution alignment between domains by utilizing the task-specific decision boundary and the Wasserstein metric.
Ranked #19 on
Image-to-Image Translation
on SYNTHIA-to-Cityscapes
Cooperative Learning with Visual Attributes
Learning paradigms involving varying levels of supervision have received a lot of interest within the computer vision and machine learning communities.
Learning Common Sense Through Visual Abstraction
We show that the commonsense knowledge we learn is complementary to what can be learnt from sources of text.
