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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