# name
Comparative study on automatic face edition

# metadata.dc.description[].value
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Sergio Escalera Guerrero

# metadata.dc.description.abstract[].value
[en] In 2018, a video of Barack Obama making a fake speech played by Jordan Pelee went viral [27], in the same year we have seen similar videos with different speeches and we have even seen how totally static images were animated, giving them a pattern to follow. That video and the other ones were made with Deep Learning technology which allowed to recreate the face of a person in the body of another or animate static faces.
Since then techniques such as deep fake, face swapping, or face motion became more popular [14], we have seen it both in the movies and on social media, and thanks to this we can see how this impacts us on a social level, for both good and bad. All of this is because Computer Science has advanced exponentially lately, what we thought impossible a few years ago, is now possible and easy to do. Research in the field of computer vision has
been very impressive and in a short time, we have gone from simply creating objects to generating artificial faces and making them replicate the patterns of behavior of other people.
This project will consist of a state-of-the-art review of these different techniques. Three methods will
be studied, all of them to edit the image that they obtain as input. It will detail the pipelines used
and will show some results, with fixed parameters, to the public to obtain a qualitative assessment
to define their faults and highlight the best of each method. And finally, a conclusion on the results
obtained and the current status of this technology as well as its social impact and the applications
that this involves.

# metadata.dc.rights[].value
memòria: cc-nc-nd (c) Richard Sudario Berrocal, 2022

# metadata.dc.rights[].value
codi: GPL (c) Richard Sudario Berrocal, 2022

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

# metadata.dc.title[].value
Comparative study on automatic face edition