SOAF: Scene Occlusion-aware Neural Acoustic Field

• URL: http://arxiv.org/abs/2407.02264v2
• Date: Wed, 3 Jul 2024 01:24:37 GMT
• Title: SOAF: Scene Occlusion-aware Neural Acoustic Field
• Authors: Huiyu Gao, Jiahao Ma, David Ahmedt-Aristizabal, Chuong Nguyen, Miaomiao Liu,
• Abstract summary: We propose a new approach called Scene Occlusion-aware Acoustic Field (SOAF) for accurate sound generation. Our approach derives a prior for sound energy field using distance-aware parametric sound-propagation modelling. We extract features from local acoustic field centred around the receiver using a Fibonacci Sphere to generate audio for novel views.
• Score: 9.651041527067907
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper tackles the problem of novel view audio-visual synthesis along an arbitrary trajectory in an indoor scene, given the audio-video recordings from other known trajectories of the scene. Existing methods often overlook the effect of room geometry, particularly wall occlusion to sound propagation, making them less accurate in multi-room environments. In this work, we propose a new approach called Scene Occlusion-aware Acoustic Field (SOAF) for accurate sound generation. Our approach derives a prior for sound energy field using distance-aware parametric sound-propagation modelling and then transforms it based on scene transmittance learned from the input video. We extract features from the local acoustic field centred around the receiver using a Fibonacci Sphere to generate binaural audio for novel views with a direction-aware attention mechanism. Extensive experiments on the real dataset RWAVS and the synthetic dataset SoundSpaces demonstrate that our method outperforms previous state-of-the-art techniques in audio generation. Project page: https://github.com/huiyu-gao/SOAF/.

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