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7319-self-supervised-generation-of-spatial-audio-for-360-video.pdf
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🔗 Source: papers.nips.cc
📊 Size: 4.26 MB
👤 Author: Pedro Morgado, Nuno Nvasconcelos, Timothy Langlois, Oliver Wang
⬇️ Downloads: 26

Summary

We introduce an approach to convert mono audio recorded by a 360◦video camera into spatial audio, a representation of the distribution of sound over the full viewing sphere, using end-to-end trainable neural networks that separate individual sound sources and localize them on the viewing sphere. Our system is conditioned on multi-modal analysis of audio and 360◦video frames, and we introduce several datasets, including one filmed ourselves and one collected in-the-wild from YouTube. During training, ground-truth spatial audio serves as self-supervision, and a mixed-down mono track forms the input to our network. We show that it is possible to infer the spatial location of sound sources based only on 360◦video and a mono audio track.

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Description

We introduce an approach to convert mono audio recorded by a 360◦video camera into spatial audio, a representation of the distribution of sound over the full...

Technical Information

  • File Format: PDF
  • File Size: 4.26 MB
  • Pages: 11
  • Language: EN
  • Author: Pedro Morgado, Nuno Nvasconcelos, Timothy Langlois, Oliver Wang
  • Total Downloads: 26
  • Last Updated: 1 month ago

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