630 citations · 2.4k across the 27 of their papers we have counts for
6 papers · 1 filter
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman, Eric Tzeng, Taesung Park +5
Domain adaptation is critical for success in new, unseen environments. Adversarial adaptation models applied in feature spaces discover domain invariant representations, but are di…
VisDA: The Visual Domain Adaptation Challenge
Xingchao Peng, Ben Usman, Neela Kaushik +3
We present the 2017 Visual Domain Adaptation (VisDA) dataset and challenge, a large-scale testbed for unsupervised domain adaptation across visual domains. Unsupervised domain adap…
Stable Distribution Alignment Using the Dual of the Adversarial Distance
Ben Usman, Kate Saenko, Brian Kulis
Methods that align distributions by minimizing an adversarial distance between them have recently achieved impressive results. However, these approaches are difficult to optimize w…
Grasp Pose Detection in Point Clouds
Andreas ten Pas, Marcus Gualtieri, Kate Saenko +1
Recently, a number of grasp detection methods have been proposed that can be used to localize robotic grasp configurations directly from sensor data without estimating object pose.…
Learning a visuomotor controller for real world robotic grasping using simulated depth images
Ulrich Viereck, Andreas ten Pas, Kate Saenko +1
We want to build robots that are useful in unstructured real world applications, such as doing work in the household. Grasping in particular is an important skill in this domain, y…
Adversarial Discriminative Domain Adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko +1
Adversarial learning methods are a promising approach to training robust deep networks, and can generate complex samples across diverse domains. They also can improve recognition d…