StereoFoley is an end-to-end video-to-stereo-audio framework that uses a base generative model fine-tuned on synthetic object-tracked data with panning and distance controls to achieve object-aware spatial sound.
Seeing and hearing: Open-domain visual-audio generation with diffusion latent aligners
2 Pith papers cite this work. Polarity classification is still indexing.
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MMAudioSep adapts a pretrained video-to-audio model via fine-tuning for video/text-queried sound separation, outperforming baselines while preserving generation ability.
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StereoFoley: Object-Aware Stereo Audio Generation from Video
StereoFoley is an end-to-end video-to-stereo-audio framework that uses a base generative model fine-tuned on synthetic object-tracked data with panning and distance controls to achieve object-aware spatial sound.