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arXiv · 2408.11915

Video-Foley: Two-Stage Video-To-Sound Generation via Temporal Event Condition For Foley Sound

Junwon Lee·Jaekwon Im·Dabin Kim·Juhan Nam
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Abstract

Foley sound synthesis is crucial for multimedia production, enhancing user experience by synchronizing audio and video both temporally and semantically. Recent studies on automating this labor-intensive process through video-to-sound generation face significant challenges. Systems lacking explicit temporal features suffer from poor alignment and controllability, while timestamp-based models require costly and subjective human annotation. We propose Video-Foley, a video-to-sound system using Root Mean Square (RMS) as an intuitive condition with semantic timbre prompts (audio or text). RMS, a frame-level intensity envelope closely related to audio semantics, acts as a temporal event feature to guide audio generation from video. The annotation-free self-supervised learning framework consists of two stages, Video2RMS and RMS2Sound, incorporating novel ideas including RMS discretization and RMS-ControlNet with a pretrained text-to-audio model. Our extensive evaluation shows that Video-Foley achieves state-of-the-art performance in audio-visual alignment and controllability for sound timing, intensity, timbre, and nuance. Source code, model weights and demos are available on our companion website. (https://jnwnlee.github.io/video-foley-demo)

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BibTeXRIS

Junwon Lee, Jaekwon Im, Dabin Kim, Juhan Nam. 2024-08-21. Video-Foley: Two-Stage Video-To-Sound Generation via Temporal Event Condition For Foley Sound. https://arxiv.org/abs/2408.11915

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