3 citations · 3 across the 1 of their papers we have counts for
3 papers
FakeBuster: A DeepFakes Detection Tool for Video Conferencing Scenarios
Vineet Mehta, Parul Gupta, Ramanathan Subramanian +1
This paper proposes a new DeepFake detector FakeBuster for detecting impostors during video conferencing and manipulated faces on social media. FakeBuster is a standalone deep lear…
The eyes know it: FakeET -- An Eye-tracking Database to Understand Deepfake Perception
Parul Gupta, Komal Chugh, Abhinav Dhall +1
We present \textbf{FakeET}-- an eye-tracking database to understand human visual perception of \emph{deepfake} videos. Given that the principal purpose of deepfakes is to deceive h…
Not made for each other- Audio-Visual Dissonance-based Deepfake Detection and Localization
Komal Chugh, Parul Gupta, Abhinav Dhall +1
We propose detection of deepfake videos based on the dissimilarity between the audio and visual modalities, termed as the Modality Dissonance Score (MDS). We hypothesize that manip…