157 citations · 159 across the 2 of their papers we have counts for
8 papers · 1 filter
Towards Measuring Fairness in AI: the Casual Conversations Dataset
Caner Hazirbas, Joanna Bitton, Brian Dolhansky +3
This paper introduces a novel dataset to help researchers evaluate their computer vision and audio models for accuracy across a diverse set of age, genders, apparent skin tones and…
Adversarial Threats to DeepFake Detection: A Practical Perspective
Paarth Neekhara, Brian Dolhansky, Joanna Bitton +1
Facially manipulated images and videos or DeepFakes can be used maliciously to fuel misinformation or defame individuals. Therefore, detecting DeepFakes is crucial to increase the…
Adversarial collision attacks on image hashing functions
Brian Dolhansky, Cristian Canton Ferrer
Hashing images with a perceptual algorithm is a common approach to solving duplicate image detection problems. However, perceptual image hashing algorithms are differentiable, and…
Adversarial Evaluation of Multimodal Models under Realistic Gray Box Assumption
Ivan Evtimov, Russel Howes, Brian Dolhansky +2
This work examines the vulnerability of multimodal (image + text) models to adversarial threats similar to those discussed in previous literature on unimodal (image- or text-only)…
The DeepFake Detection Challenge (DFDC) Dataset
Brian Dolhansky, Joanna Bitton, Ben Pflaum +4
Deepfakes are a recent off-the-shelf manipulation technique that allows anyone to swap two identities in a single video. In addition to Deepfakes, a variety of GAN-based face swapp…
Deep Poisoning: Towards Robust Image Data Sharing against Visual Disclosure
Hao Guo, Brian Dolhansky, Eric Hsin +3
Due to respectively limited training data, different entities addressing the same vision task based on certain sensitive images may not train a robust deep network. This paper intr…