SonoWorld: From One Image to a 3D Audio-Visual Scene

Derong Jin, Xiyi Chen, Ming C. Lin, Ruohan Gao
3/30/2026
cs.CVcs.MMcs.SD

No official code found. Best implementation: HuMathe/sonoworld (46 stars, MIT, last commit 2026-06-17).

Abstract

Tremendous progress in visual scene generation now turns a single image into an explorable 3D world, yet immersion remains incomplete without sound. We introduce Image2AVScene, the task of generating a 3D audio-visual scene from a single image, and present SonoWorld, the first framework to tackle this challenge. From one image, our pipeline outpaints a 360° panorama, lifts it into a navigable 3D scene, places language-guided sound anchors, and renders ambisonics for point, areal, and ambient sources, yielding spatial audio aligned with scene geometry and semantics. Quantitative evaluations on a newly curated real-world dataset and a controlled user study confirm the effectiveness of our approach. Beyond free-viewpoint audio-visual rendering, we also demonstrate applications to one-shot acoustic learning and audio-visual spatial source separation. Project website: https://humathe.github.io/sonoworld/

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Code Implementations(1)

HuMathe/sonoworldCommunity25%
MIT

Official implementation of the CVPR 2026 paper "SonoWorld: From One Image to a 3D Audio-Visual Scene."

463PythonMar 21, 20264 months agoMIT

Cite this paper

@article{jin2026sonoworld,
  title  = {SonoWorld: From One Image to a 3D Audio-Visual Scene},
  author = {Derong Jin and Xiyi Chen and Ming C. Lin and Ruohan Gao},
  year   = {2026},
  eprint = {2603.28757},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2603.28757v1}
}

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