The Power of Sound (TPoS): Audio Reactive Video Generation with Stable Diffusion

Yujin Jeong, Won-Wha Ryoo, Seunghyun Lee, Dabin Seo, Wonmin Byeon +2 more
2/14/2026

No official code found. Best implementation: eugene6923/TPoS (6 stars, last commit 2023-12-07).

Abstract

In recent years, video generation has become a prominent generative tool and has drawn significant attention. However, there is little consideration in audio-to-video generation, though audio contains unique qualities like temporal semantics and magnitude. Hence, we propose The Power of Sound (TPoS) model to incorporate audio input that includes both changeable temporal semantics and magnitude. To generate video frames, TPoS utilizes a latent stable diffusion model with textual semantic information, which is then guided by the sequential audio embedding from our pretrained Audio Encoder. As a result, this method produces audio reactive video contents. We demonstrate the effectiveness of TPoS across various tasks and compare its results with current state-of-the-art techniques in the field of audio-to-video generation. More examples are available at https://ku-vai.github.io/TPoS/

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Code Implementations(1)

eugene6923/TPoSCommunity69%

This repository is for The Power of Sound(TPoS): Audio Reactive Video Generation with Stable Diffusion (ICCV2023)

63Shell, PythonNov 3, 20232 years ago

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Cite this paper

@article{jeong2026power,
  title  = {The Power of Sound (TPoS): Audio Reactive Video Generation with Stable Diffusion},
  author = {Yujin Jeong and Won-Wha Ryoo and Seunghyun Lee and Dabin Seo and Wonmin Byeon and Sangpil Kim and Jinkyu Kim},
  year   = {2026},
  eprint = {2309.04509},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2309.04509},
  journal = {ICCV 2023 2023}
}

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