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Literature Review of Audio-Driven 2D Avatar Video Generation Algorithms

  • 2023
  • OriginalPaper
  • Chapter
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Abstract

The chapter delves into the advanced field of audio-driven 2D avatar video generation, examining the evolution from traditional methods to sophisticated deep learning algorithms. It covers talking face generation, where audio is used to create natural facial expressions and head movements, and co-speech gesture generation, which involves synthesizing body movements that align with speech content. The study also explores the use of intermediate modal representations, such as facial landmarks, to enhance the naturalness of generated videos. Additionally, it evaluates various datasets and metrics used to assess the performance of these algorithms, providing a thorough understanding of the current state and future directions in this rapidly advancing field.
This subject was supported by the Research Project of Education Commission of Beijing (KM202110015003), Initial funding for the Doctoral Program of BIGC, and Innovation team project of BIGC (Eb202103).

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Title
Literature Review of Audio-Driven 2D Avatar Video Generation Algorithms
Authors
Yuxuan Li
Han Zhang
Shaozhong Cao
Dan Jiang
Meng Wang
Weiqi Wang
Copyright Year
2023
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-99-3618-2_9
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