1 citations · 1 across the 9 of their papers we have counts for
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Hear, Localize, and Reason: Spatially Aware Scene Understanding for Audio-Visual LLMs
Kim Sung-Bin, Lee Jung-Mok, Jinwoo Jung +4
Audio-visual large language models (AV-LLMs) have made strong progress in multimodal understanding, yet most treat audio as monaural semantic content, limiting their ability to rea…
OmniSmartHome: A Multimodal Reasoning Benchmark for Smart-Home Agents
Jihoo Jung, Suho Yoo, Jeongsoo Choi +5
Smart-home assistants are expected to handle diverse, realistic requests that arise in daily life. In such interactions, users often rely on the surrounding multimodal context-poin…
SceneBind: Binding What and Where Across Vision, Audio and Language
Mingfei Chen, Zijun Cui, Ruoke Zhang +2
We present SceneBind, an omni-modal representation of realistic scenes with joint semantic and 3D spatial understanding across vision, audio and language. Existing omni-modal encod…
Seeing Through Touch: Tactile-Driven Visual Localization of Material Regions
Seongyu Kim, Seungwoo Lee, Hyeonggon Ryu +2
We address the problem of tactile localization, where the goal is to identify image regions that share the same material properties as a tactile input. Existing visuo-tactile metho…