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Rhythmic Foley: A Framework For Seamless Audio-Visual Alignment In Video-to-Audio Synthesis
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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.
Forward citations
Cited by 2 Pith papers
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AV-Link: Temporally-Aligned Diffusion Features for Cross-Modal Audio-Video Generation
AV-Link unifies video-to-audio and audio-to-video generation by aligning frozen diffusion-model activations with temporally matched rotary position embeddings in a shared Fusion Block.
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MMAudio: Taming Multimodal Joint Training for High-Quality Video-to-Audio Synthesis
A single flow-matching transformer trained jointly on audio-video and audio-text data produces state-of-the-art public video-to-audio synthesis with a frame-level synchronization module.
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