Real Face Video Animation Platform

Fuente: arXiv
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Auteurs principaux: Chen, Xiaokai, Liu, Xuan, Di, Donglin, Ma, Yongjia, Chen, Wei, Su, Tonghua
Format: Preprint
Publié: 2024
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author Chen, Xiaokai
Liu, Xuan
Di, Donglin
Ma, Yongjia
Chen, Wei
Su, Tonghua
author_facet Chen, Xiaokai
Liu, Xuan
Di, Donglin
Ma, Yongjia
Chen, Wei
Su, Tonghua
contents In recent years, facial video generation models have gained popularity. However, these models often lack expressive power when dealing with exaggerated anime-style faces due to the absence of high-quality anime-style face training sets. We propose a facial animation platform that enables real-time conversion from real human faces to cartoon-style faces, supporting multiple models. Built on the Gradio framework, our platform ensures excellent interactivity and user-friendliness. Users can input a real face video or image and select their desired cartoon style. The system will then automatically analyze facial features, execute necessary preprocessing, and invoke appropriate models to generate expressive anime-style faces. We employ a variety of models within our system to process the HDTF dataset, thereby creating an animated facial video dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2407_18955
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Real Face Video Animation Platform
Chen, Xiaokai
Liu, Xuan
Di, Donglin
Ma, Yongjia
Chen, Wei
Su, Tonghua
Computer Vision and Pattern Recognition
In recent years, facial video generation models have gained popularity. However, these models often lack expressive power when dealing with exaggerated anime-style faces due to the absence of high-quality anime-style face training sets. We propose a facial animation platform that enables real-time conversion from real human faces to cartoon-style faces, supporting multiple models. Built on the Gradio framework, our platform ensures excellent interactivity and user-friendliness. Users can input a real face video or image and select their desired cartoon style. The system will then automatically analyze facial features, execute necessary preprocessing, and invoke appropriate models to generate expressive anime-style faces. We employ a variety of models within our system to process the HDTF dataset, thereby creating an animated facial video dataset.
title Real Face Video Animation Platform
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2407.18955