论文标题
眼睛知道的：假货 - 一个引人注目的数据库，可以理解深层感知
The eyes know it: FakeET -- An Eye-tracking Database to Understand Deepfake Perception
论文作者
论文摘要
我们提出\ textbf {fakeet} - 一个眼神传播的数据库，以了解\ emph {deepfake}视频的人类视觉感知。鉴于深果的主要目的是欺骗人类的观察者，因此伪造的旨在理解和评估观众可以检测合成视频文物的便捷性。 FakeT包含从40个用户通过\ emph {tobii}桌面眼轨汇编的查看模式，用于从\ textit {google deepfake}数据集中的811个视频，每次视频中至少有两次观看。此外，还可以使用通过\ emph {Emotiv}传感器获得的脑电图响应。编译的数据确认了（a）\ emph {real} vs \ emph {face}视频的不同眼动特性； （b）眼睛轨道显着图在空间伪造的定位和检测中的效用，以及（c）与脑电图响应中误差相关的触发（c）\ emph {raw} eeg信号在区分\ emph {reamph {real}和\ emph {fake {fach} videos中的能力。
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 human observers, FakeET is designed to understand and evaluate the ease with which viewers can detect synthetic video artifacts. FakeET contains viewing patterns compiled from 40 users via the \emph{Tobii} desktop eye-tracker for 811 videos from the \textit{Google Deepfake} dataset, with a minimum of two viewings per video. Additionally, EEG responses acquired via the \emph{Emotiv} sensor are also available. The compiled data confirms (a) distinct eye movement characteristics for \emph{real} vs \emph{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 \emph{raw} EEG signal to distinguish between \emph{real} and \emph{fake} videos.
