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2026-03-02 16:38:37
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SQA3D SQA3D: Situated Question Answering in 3D Scenes Xiaojian Ma 2✶ Silong Yong 1,3✶ Zilong Zheng 1 Qing Li 1 Yitao Liang 1,4 Song-Chun Zhu 1,2,3,4 Siyuan Huang 1 ✶ indicates equal contribution 1 Beijing Institute for General Artificial Intelligence (BIGAI) 2 UCLA 3 Tsinghua University 4 Peking University arXiv | Code | Slides Abstract We propose a new task to benchmark scene understanding of embodied agents: Situated Question Answering in 3D Scenes (SQA3D). Given a scene context (e.g., 3D scan), SQA3D requires the tested agent to first understand its situation (position, orientation, etc.) in the 3D scene as described by text, then reason about its surrounding environment and answer a question under that situation. Based upon 650 scenes from ScanNet, we provide a dataset centered around 6.8k unique situations, along with 20.4k descriptions and 33.4k diverse reasoning questions ...
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