More Real than Real: A Study on Human Visual Perception of Synthetic Faces

06/14/2021
by   Federica Lago, et al.
0

Deep fakes became extremely popular in the last years, also thanks to their increasing realism. Therefore, there is the need to measures human's ability to distinguish between real and synthetic face images when confronted with cutting-edge creation technologies. We describe the design and results of a perceptual experiment we have conducted, where a wide and diverse group of volunteers has been exposed to synthetic face images produced by state-of-the-art Generative Adversarial Networks (namely, PG-GAN, StyleGAN, StyleGAN2). The experiment outcomes reveal how strongly we should call into question our human ability to discriminate real faces from synthetic ones generated through modern AI.

READ FULL TEXT

page 2

page 5

page 6

page 7

page 8

page 9

11/08/2021

A Study of the Human Perception of Synthetic Faces

Advances in face synthesis have raised alarms about the deceptive use of...
03/10/2021

Face Images as Jigsaw Puzzles: Compositional Perception of Human Faces for Machines Using Generative Adversarial Networks

An important goal in human-robot-interaction (HRI) is for machines to ac...
09/08/2020

CNN Detection of GAN-Generated Face Images based on Cross-Band Co-occurrences Analysis

Last-generation GAN models allow to generate synthetic images which are ...
04/29/2020

Stereotype-Free Classification of Fictitious Faces

Equal Opportunity and Fairness are receiving increasing attention in art...
11/05/2018

Fast Face Image Synthesis with Minimal Training

We propose an algorithm to generate realistic face im-ages of both real ...
04/01/2019

HYPE: Human eYe Perceptual Evaluation of Generative Models

Generative models often use human evaluations to determine and justify p...
04/27/2020

Preliminary Forensics Analysis of DeepFake Images

One of the most terrifying phenomenon nowadays is the DeepFake: the poss...