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Mix and Localize: Localizing Sound Sources in Mixtures

CVPR 2022 · Label-efficient and robust learning › Self-supervised and contrastive · approach: Pretext-task visual pre-training · 52 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use cycle-consistent audio-image-audio random walks instead of mixed correspondence loss (ablation)Mix and Localize · MUSIC-SyntheticCAP: 12.6 -> 34.0*Helped
use cycle-consistent audio-image-audio random walks instead of mixed correspondence loss (ablation)Mix and Localize · MUSIC-DuetCAP: 19.3 -> 47.4*Helped
use audio-image-audio cycle rather than image-sound-image cycle (ablation)Mix and Localize · MUSIC-SyntheticCAP: 11.0 -> 34.0*Helped
use audio-image-audio cycle rather than image-sound-image cycle (ablation)Mix and Localize · MUSIC-DuetCAP: 19.7 -> 47.4*Helped
use soft random-walk assignments rather than permutation-invariant hard matching (ablation)Mix and Localize · MUSIC-SyntheticCAP: 18.2* -> 34.0*Helped
use soft random-walk assignments rather than permutation-invariant hard matching (ablation)Mix and Localize · MUSIC-DuetCAP: 24.0* -> 47.4*Helped
use cycle-consistent random walks rather than OTSMix and Localize · MUSIC-SyntheticCAP: 11.4 -> 34.0*Helped
use cycle-consistent random walks rather than OTSMix and Localize · MUSIC-DuetCIoU@0.3: 13.2 -> 26.3*Helped

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