Reliability-Aware Geometric Fusion for Robust Audio-Visual Navigation
Audio-Visual Navigation (AVN) requires an embodied agent to navigate toward a sound source by utilizing both vision and binaural audio. A core challenge arises in complex acoustic environments, where binaural cues become intermittently unreliable, particularly when generalizing to previously unheard sound categories. To address this, we propose RAVN (Reliability-Aware Audio-Visual Navigation), a framework that conditions cross-modal fusion on audio-derived reliability cues, dynamically calibrating the integration of audio and visual inputs. RAVN introduces an Acoustic Geometry Reasoner (AGR) that is trained with geometric proxy supervision. Using a heteroscedastic Gaussian NLL objective, ...
| Authors | Teng Liu, Yinfeng Yu |
|---|---|
| Primary category | cs.SD |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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