Search Results for author:
Found 8 papers, 2 papers with code
Towards Measuring Fairness in AI: the Casual Conversations Dataset
The videos were recorded in multiple U. S. states with a diverse set of adults in various age, gender and apparent skin tone groups.
Adversarial Evaluation of Multimodal Models under Realistic Gray Box Assumption
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) models.
Adversarial Threats to DeepFake Detection: A Practical Perspective
We perform our evaluations on the winning entries of the DeepFake Detection Challenge (DFDC) and demonstrate that they can be easily bypassed in a practical attack scenario by designing transferable and accessible adversarial attacks.
Adversarial collision attacks on image hashing functions
Hashing images with a perceptual algorithm is a common approach to solving duplicate image detection problems.
The DeepFake Detection Challenge (DFDC) Dataset
In addition to Deepfakes, a variety of GAN-based face swapping methods have also been published with accompanying code.
Deep Poisoning: Towards Robust Image Data Sharing against Visual Disclosure
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.
The Deepfake Detection Challenge (DFDC) Preview Dataset
In this paper, we introduce a preview of the Deepfakes Detection Challenge (DFDC) dataset consisting of 5K videos featuring two facial modification algorithms.
Eye In-Painting with Exemplar Generative Adversarial Networks
This paper introduces a novel approach to in-painting where the identity of the object to remove or change is preserved and accounted for at inference time: Exemplar GANs (ExGANs).
