BatVision with GCC-PHAT Features for Better Sound to Vision Predictions

Christensen Jesper Haahr
Christensen Jesper Haahr
Hornauer Sascha
Hornauer Sascha
Cited by: 0|Bibtex|Views6|Links

Abstract:

Inspired by sophisticated echolocation abilities found in nature, we train a generative adversarial network to predict plausible depth maps and grayscale layouts from sound. To achieve this, our sound-to-vision model processes binaural echo-returns from chirping sounds. We build upon previous work with BatVision that consists of a sound...More

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