PEFS: A Validated Dataset for Perceptual Experiments on Face Swap Portrait Videos

Wöhler, Leslie; Henningson, Jann-Ole; Castillo, Susana; Magnor, Marcus

doi:10.1007/978-3-030-63426-1_13

Cited by 4 publications

(3 citation statements)

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“…The stimulus material is part of the recently released dataset for perceptual experiments on face swap portrait videos (PEFS) [7]. This dataset contains high-resolution deep fake videos that are validated through perceptual experiments.…”

Section: Stimulimentioning

confidence: 99%

“…A number of datasets have been created to evaluate the performance of forensic fake detection methods, e.g. [7,8]. For our experiment, we base our stimuli on the PEFS dataset [7] that contains actors that our participants are highly familiar with, i.e., co-workers for longer than two years.…”

Section: Introductionmentioning

confidence: 99%

“…[7,8]. For our experiment, we base our stimuli on the PEFS dataset [7] that contains actors that our participants are highly familiar with, i.e., co-workers for longer than two years.…”

Section: Introductionmentioning

confidence: 99%

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EEG-Based Analysis of the Impact of Familiarity in the Perception of Deepfake Videos

Tauscher

Castillo

Bosse

et al. 2021

2021 IEEE International Conference on Image Processing (ICIP)

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We investigate the brain's subliminal response to fake portrait videos using electroencephalography, with a special emphasis on the viewer's familiarity with the depicted individuals.Deepfake videos are increasingly becoming popular but, while they are entertaining, they can also pose a threat to society. These face-swapped videos merge physiognomy and behaviour of two different individuals, both strong cues used for recognizing a person. We show that this mismatch elicits different brain responses depending on the viewer's familiarity with the merged individuals.Using EEG, we classify perceptual differences of familiar and unfamiliar people versus their face-swapped counterparts. Our results show that it is possible to discriminate fake videos from genuine ones when at least one face-swapped actor is known to the observer. Furthermore, we indicate a correlation of classification accuracy with level of personal engagement between participant and actor, as well as with the participant's familiarity with the used dataset.

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Section: Stimulimentioning

confidence: 99%