Controlling Face's Frame generation in StyleGAN's latent space operations: Modifying faces to deceive our memory
Agust\'in Roca, Nicol\'as Ignacio Britos

TL;DR
This paper investigates how modifications in StyleGAN2-generated faces affect the face's frame, aiming to understand their impact on human memory and the potential for deception in face recognition tasks.
Contribution
It introduces methods to identify and compare face-frames in StyleGAN2 faces and analyzes how various attribute modifications influence frame stability.
Findings
Face-frame remains stable when altering eye and mouth openness.
Vertical face orientation, gender, age, and smile significantly affect frame variation.
Horizontal face orientation has the largest impact on face-frame changes.
Abstract
Innocence Project is a non-profitable organization that works in reducing wrongful convictions. In collaboration with Laboratorio de Sue\~no y Memoria from Instituto Tecnol\'ogico de Buenos Aires (ITBA), they are studying human memory in the context of face identification. They have a strong hypothesis stating that human memory heavily relies in face's frame to recognize faces. If this is proved, it could mean that face recognition in police lineups couldn't be trusted, as they may lead to wrongful convictions. This study uses experiments in order to try to prove this using faces with different properties, such as eyes size, but maintaining its frame as much as possible. In this project, we continue the work from a previous project that provided the basic tool to generate realistic faces using StyleGAN2. We take a deep dive into the internals of this tool to make full use of StyleGAN2…
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Taxonomy
TopicsSocial Robot Interaction and HRI · Deception detection and forensic psychology · Speech and dialogue systems
MethodsWeight Demodulation · Path Length Regularization · HuMan(Expedia)||How do I get a human at Expedia? · R1 Regularization · Convolution
