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Visual Acoustic Matching
[article]
2022
arXiv
pre-print
We introduce the visual acoustic matching task, in which an audio clip is transformed to sound like it was recorded in a target environment. Given an image of the target environment and a waveform for the source audio, the goal is to re-synthesize the audio to match the target room acoustics as suggested by its visible geometry and materials. To address this novel task, we propose a cross-modal transformer model that uses audio-visual attention to inject visual properties into the audio and
arXiv:2202.06875v2
fatcat:qt6he2ckazgaxp6chln2m73kwa