Paper ID: 2409.08628

Rhythmic Foley: A Framework For Seamless Audio-Visual Alignment In Video-to-Audio Synthesis

Zhiqi Huang, Dan Luo, Jun Wang, Huan Liao, Zhiheng Li, Zhiyong Wu

Our research introduces an innovative framework for video-to-audio synthesis, which solves the problems of audio-video desynchronization and semantic loss in the audio. By incorporating a semantic alignment adapter and a temporal synchronization adapter, our method significantly improves semantic integrity and the precision of beat point synchronization, particularly in fast-paced action sequences. Utilizing a contrastive audio-visual pre-trained encoder, our model is trained with video and high-quality audio data, improving the quality of the generated audio. This dual-adapter approach empowers users with enhanced control over audio semantics and beat effects, allowing the adjustment of the controller to achieve better results. Extensive experiments substantiate the effectiveness of our framework in achieving seamless audio-visual alignment.

Submitted: Sep 13, 2024