Paper Info
Title
The eyes know it: FakeET -- An Eye-tracking Database to Understand Deepfake Perception
Abstract
We present FakeET -- an eye-tracking database to understand human visual perception of deepfake videos. Given that the principal purpose of deepfakes is to deceive human observers, FakeET is designed to understand and evaluate the ability of viewers to detect synthetic video artifacts. FakeET contains viewing patterns compiled from 40 users via the Tobii desktop eye-tracker for 811 videos from the Google Deepfake dataset, with a minimum of two viewings per video. Additionally, EEG responses acquired via the Emotiv sensor are also available. The compiled data confirms (a) distinct eye movement characteristics for real vs fake videos; (b) utility of the eye-track saliency maps for spatial forgery localization and detection, and (c) Error Related Negativity (ERN) triggers in the EEG responses, and the ability of the raw EEG signal to distinguish between real and fake videos.
Year
DOI
Venue
2020
10.1145/3382507.3418857
ICMI '20: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION Virtual Event Netherlands October, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-7581-8
1
PageRank 
References 
Authors
0.39
9
4
Name
Order
Citations
PageRank
Parul Gupta1929.30
Chugh Komal210.39
Abhinav Dhall3103552.61
Ramanathan Subramanian464.63