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{\deg} 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/
@article{arxiv.2603.28757,
title = {SonoWorld: From One Image to a 3D Audio-Visual Scene},
author = {Derong Jin and Xiyi Chen and Ming C. Lin and Ruohan Gao},
journal= {arXiv preprint arXiv:2603.28757},
year = {2026}
}
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Accepted by CVPR 2026, project page: https://humathe.github.io/sonoworld/