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Sound Source Localization is All about Cross-Modal Alignment

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Humans can easily perceive the direction of sound sources in a visual scene, termed sound source localization. Recent studies on learning-based sound source localization have mainly explored the problem from a localization perspective. However, prior arts and existing benchmarks do not account for a more important aspect of the problem, cross-modal semantic understanding, which is essential for genuine sound source localization. Cross-modal semantic understanding is important in understanding semantically mismatched audio-visual events, e.g., silent objects, or off-screen sounds. To account for this, we propose a cross-modal alignment task as a joint task with sound source localization to better learn the interaction between audio and visual modalities. Thereby, we achieve high localization performance with strong cross-modal semantic understanding. Our method outperforms the state-of-the-art approaches in both sound source localization and cross-modal retrieval. Our work suggests that jointly tackling both tasks is necessary to conquer genuine sound source localization.

Arda Senocak, Hyeonggon Ryu, Junsik Kim, Tae-Hyun Oh, Hanspeter Pfister, Joon Son Chung• 2023

Related benchmarks

TaskDatasetResultRank
Sound Source LocalizationFlickr SoundNet (test)
CIoU82.4
28
Single-source sound localizationVGGSound single-source (test)
IoU@0.550.8
23
Multi-sound source localizationMUSIC-Duet (test)
CIoU@0.338.3
23
Multi-sound source localizationVGGSound-Duet (test)
CIoU@0.335.8
23
Sound LocalizationMUSIC-Solo 1.0 (test)
IoU@0.566.4
22
Single-source sound localizationVGGSound Instruments (test)
IoU@0.365.8
13
Multi-source sound localizationVGGSound Instruments (test)
CIoU@0.184.9
13
Audio referred image groundingVGG-SS (test)
cIoU42.64
10
Audio referred image groundingPascalSound (test)
cIoU58.34
10
Audio referred image groundingAVSBench (test)
cIoU71.57
10
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