Avatar customization using deep learning’s style transfer technology
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/158176
comunitat-uji-handle2:10234/71324
comunitat-uji-handle3:10234/169451
comunitat-uji-handle4:
TFG-TFMMetadatos
Título
Avatar customization using deep learning’s style transfer technologyAutoría
Tutor/Supervisor; Universidad.Departamento
Fernández Beltrán, Rafael; Universitat Jaume I. Departament de Llenguatges i Sistemes InformàticsFecha de publicación
2023-07-18Editor
Universitat Jaume IResumen
An important aspect in the world of video games is the player's identity, In this regard
player´s avatar plays a significant role in this. However, we often find ourselves limited to a
few predefined options, which ... [+]
An important aspect in the world of video games is the player's identity, In this regard
player´s avatar plays a significant role in this. However, we often find ourselves limited to a
few predefined options, which can restrict our individual expression. This document presents
a project report on an application aiming to address this issue by providing more
customization options to players. This application, developed in tkinter, utilizes a Style
Transfer Model [1] using deep learning techniques (Specifically Convolutional Neural
Networks) to transform user’s self images into a specific artistic style.
Also, it offers a user-friendly interface where users can upload their avatar images or take a
photo, and choose from a predefined list of artistic styles. Once the desired style is selected,
the application applies the style transfer model to generate the transformed image. [-]
Palabras clave / Materias
Descripción
Treball final de Grau en Disseny i Desenvolupament de Videojocs. Codi: VJ1241. Curs acadèmic: 2022/2023
Tipo de documento
info:eu-repo/semantics/bachelorThesisDerechos de acceso
info:eu-repo/semantics/openAccess