AI RESEARCH
CounterFlow: A Two-Phase Inference-Time Sampling for Counterfactual Video Foley Generation
arXiv CS.AI
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ArXi:2605.18916v1 Announce Type: cross We investigate Counterfactual Video Foley Generation, which aims to adopt a sound-source identity that contradicts the visual evidence while remaining temporally synchronized to a silent video. Existing Video&Text-to-Audio (VT2A) models struggle with this, often remaining anchored to the visually implied sound source when video and text contents disagree. We present ConterFlow, an inference-time dual-phase sampling scheme for pretrained flow-matching VT2A models.