# Acoustic Volume Rendering for Neural Impulse Response Fields

arXiv: https://arxiv.org/abs/2411.06307 · HTML: https://mlsanity.com/paper/2411.06307/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Nov 2024.

## Built on by (most cited first, 14 of 14)

- [MOSPA: Human Motion Generation Driven by Spatial Audio](https://mlsanity.com/paper/2507.11949/) (2025)
- [Guiding Audio Editing with Audio Language Model](https://mlsanity.com/paper/2509.21625/) (2025)
- [Hearing Anywhere in Any Environment](https://mlsanity.com/paper/2504.10746/) (2025)
- [Differentiable Room Acoustic Rendering with Multi-View Vision Priors](https://mlsanity.com/paper/2504.21847/) (2025)
- [Next-Scale Autoregressive Models for Text-to-Motion Generation](https://mlsanity.com/paper/2604.03799/) (2026)
- [SonoWorld: From One Image to a 3D Audio-Visual Scene](https://mlsanity.com/paper/2603.28757/) (2026)
- [Scalable RF Simulation in Generative 4D Worlds](https://mlsanity.com/paper/2508.12176/) (2025)
- [Enhancing XR Auditory Realism via Multimodal Scene-Aware Acoustic Rendering](https://mlsanity.com/paper/2511.11930/) (2025)
- [Resounding Acoustic Fields with Reciprocity](https://mlsanity.com/paper/2510.20602/) (2025)
- [Active noise cancellation on open-ear smart glasses](https://mlsanity.com/paper/2604.05519/) (2026)
- [EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction](https://mlsanity.com/paper/2605.28101/) (2026)
- [Scene2Sound: Auditory-Grounded Soundscape Generation for 3D Gaussian Worlds](https://mlsanity.com/paper/2608.00463/) (2026)
- [Reconstructing the Vocal Tract with Differentiable Acoustic Simulation](https://mlsanity.com/paper/2609.36737/) (2026)
- [Audible World Models: Spatially Aware Sound Generation for 3D Worlds](https://mlsanity.com/paper/2609.38444/) (2026)

## Abstract (arXiv)

Realistic audio synthesis that captures accurate acoustic phenomena is essential for creating immersive experiences in virtual and augmented reality. Synthesizing the sound received at any position relies on the estimation of impulse response (IR), which characterizes how sound propagates in one scene along different paths before arriving at the listener's position. In this paper, we present Acoustic Volume Rendering (AVR), a novel approach that adapts volume rendering techniques to model acoustic impulse responses. While volume rendering has been successful in modeling radiance fields for images and neural scene representations, IRs present unique challenges as time-series signals. To address these challenges, we introduce frequency-domain volume rendering and use spherical integration to fit the IR measurements. Our method constructs an impulse response field that inherently encodes wave propagation principles and achieves state-of-the-art performance in synthesizing impulse responses for novel poses. Experiments show that AVR surpasses current leading methods by a substantial margin. Additionally, we develop an acoustic simulation platform, AcoustiX, which provides more accurate and realistic IR simulations than existing simulators. Code for AVR and AcoustiX are available at https://zitonglan.github.io/avr.