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| Format: | Preprint |
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2024
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| Online Access: | https://arxiv.org/abs/2407.00803 |
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| _version_ | 1866917708926287872 |
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| author | Roca, Agustín Britos, Nicolás Ignacio |
| author_facet | Roca, Agustín Britos, Nicolás Ignacio |
| contents | Innocence Project is a non-profitable organization that works in reducing wrongful convictions. In collaboration with Laboratorio de Sueño y Memoria from Instituto Tecnológico 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 functionalities, while also adding more features, such as modifying certain of its attributes, including mouth-opening or eye-opening.
As the usage of this tool heavily relies on maintaining the face-frame, we develop a way to identify the face-frame of each image and a function to compare it to the output of the neural network after applying some operations.
We conclude that the face-frame is maintained when modifying eye-opening or mouth opening. When modifying vertical face orientation, gender, age and smile, have a considerable impact on its frame variation. And finally, the horizontal face orientation shows a major impact on the face-frame. This way, the Lab may apply some operations being confident that the face-frame won't significantly change, making them viable to be used to deceive subjects' memories. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_00803 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Controlling Face's Frame generation in StyleGAN's latent space operations: Modifying faces to deceive our memory Roca, Agustín Britos, Nicolás Ignacio Computer Vision and Pattern Recognition Artificial Intelligence Innocence Project is a non-profitable organization that works in reducing wrongful convictions. In collaboration with Laboratorio de Sueño y Memoria from Instituto Tecnológico 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 functionalities, while also adding more features, such as modifying certain of its attributes, including mouth-opening or eye-opening. As the usage of this tool heavily relies on maintaining the face-frame, we develop a way to identify the face-frame of each image and a function to compare it to the output of the neural network after applying some operations. We conclude that the face-frame is maintained when modifying eye-opening or mouth opening. When modifying vertical face orientation, gender, age and smile, have a considerable impact on its frame variation. And finally, the horizontal face orientation shows a major impact on the face-frame. This way, the Lab may apply some operations being confident that the face-frame won't significantly change, making them viable to be used to deceive subjects' memories. |
| title | Controlling Face's Frame generation in StyleGAN's latent space operations: Modifying faces to deceive our memory |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2407.00803 |