9 citations · 19 across the 5 of their papers we have counts for
5 papers
Sequential training of GANs against GAN-classifiers reveals correlated "knowledge gaps" present among independently trained GAN instances
Arkanath Pathak, Nicholas Dufour
Modern Generative Adversarial Networks (GANs) generate realistic images remarkably well. Previous work has demonstrated the feasibility of "GAN-classifiers" that are distinct from…
TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization
Fabrizio Guillaro, Davide Cozzolino, Avneesh Sud +2
In this paper we present TruFor, a forensic framework that can be applied to a large variety of image manipulation methods, from classic cheapfakes to more recent manipulations bas…
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
Ben Usman, Avneesh Sud, Nick Dufour +1
Distribution alignment has many applications in deep learning, including domain adaptation and unsupervised image-to-image translation. Most prior work on unsupervised distribution…
Cross-Domain Image Manipulation by Demonstration
Ben Usman, Nick Dufour, Kate Saenko +1
In this work we propose a model that can manipulate individual visual attributes of objects in a real scene using examples of how respective attribute manipulations affect the outp…
Eyemotion: Classifying facial expressions in VR using eye-tracking cameras
Steven Hickson, Nick Dufour, Avneesh Sud +2
One of the main challenges of social interaction in virtual reality settings is that head-mounted displays occlude a large portion of the face, blocking facial expressions and ther…