Identify, Locate and Separate: Audio-Visual Object Extraction in
Large Video Collections using Weak Supervision

Sanjeel Parekh  Alexey Ozerov  Slim Essid  Ngoc Duong  Patrick Pérez  Gaël Richard

WASPAA 2019 Supplementary Material

Visual Localization Examples





Some failure cases (video ground truth class in red )

object (harmonica) too small and occluded
multiple object instance grouping and visual clutter (bagpipes and violin)
intra-class variation (xylophone) and visual clutter

Source Separation Examples

Computed using audio-only NCP system in "Label Known" mode

Separating instrument sounds from "in-the-wild" YouTube videos
We perform hard thresholding ( τ = 0.1, as explained in the paper). Note that there is no assumption on the number of sources in the mixture.

For each separation result below the NMF is randomly initialized.

To play the audio click on the link between square brackets [ ]

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