Sound Source Localization is All about Cross-Modal Alignment
Senocak, Arda, Ryu, Hyeonggon, Kim, Junsik, Oh, Tae-Hyun, Pfister, Hanspeter, Chung, Joon Son
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Sep-19-2023
- Country:
- Asia (0.04)
- Europe > Netherlands
- North Holland > Amsterdam (0.04)
- Genre:
- Research Report > Promising Solution (0.34)
- Technology:
- Information Technology > Artificial Intelligence
- Vision (1.00)
- Natural Language (0.93)
- Machine Learning > Statistical Learning (0.46)
- Information Technology > Artificial Intelligence