The Power of Sound (TPoS): Audio Reactive Video Generation with Stable Diffusion
This addresses the problem of generating video from audio for applications in multimedia and AI, representing an incremental advance in a niche area.
The paper tackles audio-to-video generation by proposing The Power of Sound (TPoS) model, which incorporates audio input with temporal semantics and magnitude to guide a latent stable diffusion model, resulting in audio-reactive video content and demonstrating effectiveness compared to state-of-the-art techniques.
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/