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

November 06, 2022 ยท Entered Twilight ยท ๐Ÿ› IEEE Workshop/Winter Conference on Applications of Computer Vision

๐Ÿ’ค TWILIGHT: Eternal Rest
Repo abandoned since publication

Repo contents: .gitignore, LICENSE, README.md, datamodule.py, datasets_flow.py, figures, metadata, model.py, preprocess, requirements.txt, test.py, train.py

Authors Dennis Fedorishin, Deen Dayal Mohan, Bhavin Jawade, Srirangaraj Setlur, Venu Govindaraju arXiv ID 2211.03019 Category cs.CV: Computer Vision Citations 14 Venue IEEE Workshop/Winter Conference on Applications of Computer Vision Repository https://github.com/denfed/heartheflow โญ 12 Last Checked 1 month ago
Abstract
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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

๐Ÿ“œ Similar Papers

In the same crypt โ€” Computer Vision