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arXiv Computer Vision By Kim Sung-Bin, Lee Jung-Mok, Jinwoo Jung, Oh Hyun-Bin, Hyeonggon Ryu, David Harwath, Tae-Hyun Oh

Hear, Localize, and Reason: Spatially Aware Scene Understanding for Audio-Visual LLMs

Read the original on arXiv Computer Vision →

The paper introduces HLR-AVSceneQA, a benchmark that tests audio‑visual large language models on a hear‑localize‑reason hierarchy, assessing recognition of sounds, localization in egocentric and allocentric views, and reasoning about their relation to the visual scene. It also presents HLR‑LLM, a model that adds a binaural spatial audio branch to a strong audio‑visual foundation and is trained with a curriculum including chain‑of‑thought supervision for multi‑step spatial reasoning. Experiments show that existing AV‑LLMs are limited in spatial grounding and relational reasoning, while HLR‑LLM markedly improves spatial audio‑visual scene understanding without hurting semantic perception.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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