# StereoFoley: Object-Aware Stereo Audio Generation from Video

arXiv: https://arxiv.org/abs/2509.18272 · HTML: https://mlsanity.com/paper/2509.18272/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Sep 2025.

## Built on by (most cited first, 4 of 4)

- [Foley Control: Aligning a Frozen Latent Text-to-Audio Model to Video](https://mlsanity.com/paper/2510.21581/) (2025)
- [PAVAS: Physics-Aware Video-to-Audio Synthesis](https://mlsanity.com/paper/2512.08282/) (2025)
- [Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer](https://mlsanity.com/paper/2605.30940/) (2026)
- [WorldSonus: Bringing Sound to Worlds](https://mlsanity.com/paper/2610.08760/) (2026)

## Abstract (arXiv)

We present StereoFoley, a video-to-audio generation framework that produces semantically aligned, temporally synchronized, and spatially accurate stereo sound at 48 kHz. While recent generative video-to-audio models achieve strong semantic and temporal fidelity, they largely remain limited to mono or fail to deliver object-aware stereo imaging, constrained by the lack of professionally mixed, spatially accurate video-to-audio datasets. First, we develop a base model that generates stereo audio from video, achieving performance on par with state-of-the-art V2A models in both semantic accuracy and synchronization. Next, to overcome dataset limitations, we introduce a synthetic data generation pipeline that combines video analysis, object tracking, and audio synthesis with dynamic panning and distance-based loudness controls, enabling spatially accurate object-aware sound. Finally, we fine-tune the base model on this synthetic dataset, yielding clear object-audio correspondence. Since no established metrics exist, we introduce a stereo object-awareness metric and report it alongside a human listening study; the two evaluations exhibit consistent trends. This work establishes the first end-to-end framework for stereo object-aware video-to-audio generation, addressing a critical gap in the field.