arXiv Computer Vision By Juno Kim, Yesol Park, Hye-Jung Yoon, Byoung-Tak Zhang

Scene-Q: Confidence-Aware Coarse-to-Fine Querying of 3D Scenes with Selective VLM Reasoning

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Scene-Q is a confidence‑aware, coarse‑to‑fine querying framework for indoor mobile robots that grounds natural‑language queries in a 3D map. It normalizes encoder scores with temperature scaling and only invokes a reasoning VLM for low‑confidence cases, while high‑confidence queries are answered by fast retrieval. The method improves open‑vocabulary 3D instance segmentation on ScanNet200 and natural‑language 3D instance retrieval on real‑world reconstructions, especially for spatial and relational queries, while maintaining a substantial fraction of queries on the fast path.

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