Mix and Localize: Localizing Sound Sources in Mixtures
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Abstract (arXiv)
We present a method for simultaneously localizing multiple sound sources within a visual scene. This task requires a model to both group a sound mixture into individual sources, and to associate them with a visual signal. Our method jointly solves both tasks at once, using a formulation inspired by the contrastive random walk of Jabri et al. We create a graph in which images and separated sounds correspond to nodes, and train a random walker to transition between nodes from different modalities with high return probability. The transition probabilities for this walk are determined by an audio-visual similarity metric that is learned by our model. We show through experiments with musical instruments and human speech that our model can successfully localize multiple sounds, outperforming other self-supervised methods. Project site: https://hxixixh.github.io/mix-and-localize
Key facts. Cited by 54 papers in the map (data through 14 Oct 2026). Builds on 43 of its 54 references that are in the map. First posted on arXiv 28 Nov 2022.
Builds on
43 of 54 references.
References · 43
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
- 2015Learning Deep Features for Discriminative Localizationcited by 2,436
- 2018Unsupervised Feature Learning via Non-Parametric Instance-level Discriminationcited by 1,845
- 2018VoxCeleb2: Deep Speaker Recognitioncited by 875
- 2020VGGSound: A Large-scale Audio-Visual Datasetcited by 648
- 2017Look, Listen and Learncited by 458
- 2018Audio-Visual Scene Analysis with Self-Supervised Multisensory Featurescited by 335
- 2019Learning Correspondence from the Cycle-Consistency of Timecited by 269
- 2018The Sound of Pixelscited by 259
- 2017Objects that Soundcited by 256
31 more
- 2018Cooperative Learning of Audio and Video Models from Self-Supervised Synchronizationcited by 249
- 2016SoundNet: Learning Sound Representations from Unlabeled Videocited by 247
- 2020Space-Time Correspondence as a Contrastive Random Walkcited by 239
- 2015Deep clustering: Discriminative embeddings for segmentation and separationcited by 212
- 2016Permutation Invariant Training of Deep Models for Speaker-Independent Multi-talker Speech Separationcited by 191
- 2018Learning to Localize Sound Source in Visual Scenescited by 189
- 2020Self-Supervised Learning of Audio-Visual Objects from Videocited by 188
- 2021Localizing Visual Sounds the Hard Waycited by 170
- 2018Tracking Emerges by Colorizing Videoscited by 166
- 2019The Sound of Motionscited by 146
- 2020Audiovisual SlowFast Networks for Video Recognitioncited by 146
- 2015Visually Indicated Soundscited by 128
- 2018Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separationcited by 125
- 2020Multiple Sound Sources Localization from Coarse to Finecited by 118
- 2021VisualVoice: Audio-Visual Speech Separation with Cross-Modal Consistencycited by 114
- 2018The Conversation: Deep Audio-Visual Speech Enhancementcited by 109
- 2020Evaluating Weakly Supervised Object Localization Methods Rightcited by 105
- 2020Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matchingcited by 104
- 2020Labelling unlabelled videos from scratch with multi-modal self-supervisioncited by 100
- 2018Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Inputcited by 81
- 2017Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learningcited by 67
- 2018Seeing Voices and Hearing Faces: Cross-modal biometric matchingcited by 60
- 2021Cyclic Co-Learning of Sounding Object Visual Grounding and Sound Separationcited by 59
- 2020VisualEchoes: Spatial Image Representation Learning through Echolocationcited by 55
- 2019Self-Supervised Audio-Visual Co-Segmentationcited by 44
- 2021There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledgecited by 44
- 2020Telling Left from Right: Learning Spatial Correspondence of Sight and Soundcited by 43
- 2022Learning Pixel Trajectories with Multiscale Contrastive Random Walkscited by 36
- 2021Move2Hear: Active Audio-Visual Source Separationcited by 35
- 2021Visual Scene Graphs for Audio Source Separationcited by 29
- 2021Structure from Silence: Learning Scene Structure from Ambient Soundcited by 17
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Citing papers per year: 2022: 1; 2023: 18; 2024: 17; 2025: 16; 2026: 2.
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- 2025Implicit Counterfactual Learning for Audio-Visual Segmentation28 Jul 2025
- 2025What's Making That Sound Right Now? Video-centric Audio-Visual Localization7 Jul 2025
- 2025Revisiting Audio-Visual Segmentation with Vision-Centric Transformer30 Jun 2025
- 2025DEL: Dense Event Localization for Multi-modal Audio-Visual Understanding29 Jun 2025
- 2025Object-aware Sound Source Localization via Audio-Visual Scene Understanding23 Jun 2025
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