# LAVSS: Location-Guided Audio-Visual Spatial Audio Separation

arXiv: https://arxiv.org/abs/2310.20446 · HTML: https://mlsanity.com/paper/2310.20446/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 55 of its 81 references that are in the map.
- First posted on arXiv 31 Oct 2023.

## Builds on (most cited first, 30 of 55)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [Learning Deep Features for Discriminative Localization](https://mlsanity.com/paper/1512.04150/) (2015)
- [Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation](https://mlsanity.com/paper/1809.07454/) (2018)
- [AudioGen: Textually Guided Audio Generation](https://mlsanity.com/paper/2209.15352/) (2022)
- [The Sound of Pixels](https://mlsanity.com/paper/1804.03160/) (2018)
- [EPIC-Fusion: Audio-Visual Temporal Binding for Egocentric Action Recognition](https://mlsanity.com/paper/1908.08498/) (2019)
- [Learning to Localize Sound Source in Visual Scenes](https://mlsanity.com/paper/1803.03849/) (2018)
- [The Sound of Motions](https://mlsanity.com/paper/1904.05979/) (2019)
- [SCSampler: Sampling Salient Clips from Video for Efficient Action Recognition](https://mlsanity.com/paper/1904.04289/) (2019)
- [Multiple Sound Sources Localization from Coarse to Fine](https://mlsanity.com/paper/2007.06355/) (2020)
- [TasNet: time-domain audio separation network for real-time, single-channel speech separation](https://mlsanity.com/paper/1711.00541/) (2017)
- [Learning to Separate Object Sounds by Watching Unlabeled Video](https://mlsanity.com/paper/1804.01665/) (2018)
- [VisualVoice: Audio-Visual Speech Separation with Cross-Modal Consistency](https://mlsanity.com/paper/2101.03149/) (2021)
- [Music Gesture for Visual Sound Separation](https://mlsanity.com/paper/2004.09476/) (2020)
- [Co-Separating Sounds of Visual Objects](https://mlsanity.com/paper/1904.07750/) (2019)
- [Visual to Sound: Generating Natural Sound for Videos in the Wild](https://mlsanity.com/paper/1712.01393/) (2017)
- [Self-Supervised Generation of Spatial Audio for 360 Video](https://mlsanity.com/paper/1809.02587/) (2018)
- [Foley Music: Learning to Generate Music from Videos](https://mlsanity.com/paper/2007.10984/) (2020)
- [Deep Audio-Visual Learning: A Survey](https://mlsanity.com/paper/2001.04758/) (2020)
- [Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learning](https://mlsanity.com/paper/1712.07271/) (2017)
- [Learning Neural Acoustic Fields](https://mlsanity.com/paper/2204.00628/) (2022)
- [2.5D Visual Sound](https://mlsanity.com/paper/1812.04204/) (2018)
- [Self-supervised Moving Vehicle Tracking with Stereo Sound](https://mlsanity.com/paper/1910.11760/) (2019)
- [Look, Listen, and Attend: Co-Attention Network for Self-Supervised Audio-Visual Representation Learning](https://mlsanity.com/paper/2008.05789/) (2020)
- [Seeing Voices and Hearing Faces: Cross-modal biometric matching](https://mlsanity.com/paper/1804.00326/) (2018)
- [Cyclic Co-Learning of Sounding Object Visual Grounding and Sound Separation](https://mlsanity.com/paper/2104.02026/) (2021)
- [Sep-Stereo: Visually Guided Stereophonic Audio Generation by Associating Source Separation](https://mlsanity.com/paper/2007.09902/) (2020)

## Built on by (most cited first, 8 of 8)

- [SEE-2-SOUND: Zero-Shot Spatial Environment-to-Spatial Sound](https://mlsanity.com/paper/2406.06612/) (2024)
- [Continual Audio-Visual Sound Separation](https://mlsanity.com/paper/2411.02860/) (2024)
- [Multi-Source Spatial Knowledge Understanding for Immersive Visual Text-to-Speech](https://mlsanity.com/paper/2410.14101/) (2024)
- [SOAF: Scene Occlusion-aware Neural Acoustic Field](https://mlsanity.com/paper/2407.02264/) (2024)
- [SoundVista: Novel-View Ambient Sound Synthesis via Visual-Acoustic Binding](https://mlsanity.com/paper/2504.05576/) (2025)
- [UWAV: Uncertainty-weighted Weakly-supervised Audio-Visual Video Parsing](https://mlsanity.com/paper/2505.09615/) (2025)
- [MARS-Sep: Multimodal-Aligned Reinforced Sound Separation](https://mlsanity.com/paper/2510.10509/) (2025)
- [SceneBind: Binding What and Where Across Vision, Audio and Language](https://mlsanity.com/paper/2607.15265/) (2026)

## Abstract (arXiv)

Existing machine learning research has achieved promising results in monaural audio-visual separation (MAVS). However, most MAVS methods purely consider what the sound source is, not where it is located. This can be a problem in VR/AR scenarios, where listeners need to be able to distinguish between similar audio sources located in different directions. To address this limitation, we have generalized MAVS to spatial audio separation and proposed LAVSS: a location-guided audio-visual spatial audio separator. LAVSS is inspired by the correlation between spatial audio and visual location. We introduce the phase difference carried by binaural audio as spatial cues, and we utilize positional representations of sounding objects as additional modality guidance. We also leverage multi-level cross-modal attention to perform visual-positional collaboration with audio features. In addition, we adopt a pre-trained monaural separator to transfer knowledge from rich mono sounds to boost spatial audio separation. This exploits the correlation between monaural and binaural channels. Experiments on the FAIR-Play dataset demonstrate the superiority of the proposed LAVSS over existing benchmarks of audio-visual separation. Our project page: https://yyx666660.github.io/LAVSS/.