SonicVista: Generating a 4D Audio-Visual Scene from One Video via Diffusion Synchronization

Recent progress in visual scene generation has begun to move beyond static 3D scenes toward the more challenging problem of generating dynamic 4D scenes from minimal input. However, sound, despite being intrinsically coupled with dynamic objects and events, remains largely unmodeled in prior work. We present V2AVS, a new task that turns a video into an exploratable, time-varying 4D audio-visual scene, and SonicVista, the first framework for this task. From an input monocular video, our method generates a 360-degree static background, reconstructs explicit motion trajectories of dynamic foreground sounding objects, and synthesizes a physically-grounded, multi-source consistent sound field through dual-space audio diffusion synchronization. The resulting 4D scene supports both real-time novel-view visual rendering and spatial audio rendering. Evaluations on real-world datasets show that SonicVista achieves the state-of-the-art spatial audio rendering quality and geometry-grounded audio-visual consistency in generated 4D audio-visual scenes.