mlsanityData to 7 Oct 2026

Hear The Flow: Optical Flow-Based Self-Supervised Visual Sound Source Localization

arXiv 2211.03019 ↗First posted 6 Nov 2022cs.CVcited by 14

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Abstract (arXiv)

Learning to localize the sound source in videos without explicit annotations is a novel area of audio-visual research. Existing work in this area focuses on creating attention maps to capture the correlation between the two modalities to localize the source of the sound. In a video, oftentimes, the objects exhibiting movement are the ones generating the sound. In this work, we capture this characteristic by modeling the optical flow in a video as a prior to better aid in localizing the sound source. We further demonstrate that the addition of flow-based attention substantially improves visual sound source localization. Finally, we benchmark our method on standard sound source localization datasets and achieve state-of-the-art performance on the Soundnet Flickr and VGG Sound Source datasets. Code: https://github.com/denfed/heartheflow.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 24 of its 35 references that are in the map. First posted on arXiv 6 Nov 2022.

Builds on

24 of 35 references.

References · 24

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  4. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  5. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  6. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,712
  7. 2015Fast R-CNNcited by 2,930
  8. 2015Learning Deep Features for Discriminative Localizationcited by 2,430
  9. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  10. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,054
  11. 2020VGGSound: A Large-scale Audio-Visual Datasetcited by 641
  12. 2021SLIP: Self-supervision meets Language-Image Pre-trainingcited by 434
12 more
  1. 2021VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Textcited by 427
  2. 2018Audio-Visual Scene Analysis with Self-Supervised Multisensory Featurescited by 335
  3. 2017Objects that Soundcited by 254
  4. 2016SoundNet: Learning Sound Representations from Unlabeled Videocited by 244
  5. 2018Learning to Localize Sound Source in Visual Scenescited by 188
  6. 2020Self-Supervised Learning of Audio-Visual Objects from Videocited by 186
  7. 2021Localizing Visual Sounds the Hard Waycited by 169
  8. 2019Listen to Look: Action Recognition by Previewing Audiocited by 163
  9. 2019The Sound of Motionscited by 145
  10. 2020Multiple Sound Sources Localization from Coarse to Finecited by 118
  11. 2022Learning Sound Localization Better From Semantically Similar Samplescited by 32
  12. 2022Self-Supervised Predictive Learning: A Negative-Free Method for Sound Source Localization in Visual Scenescited by 31

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 5; 2025: 4; 2026: 1.

14 papers.

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