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ScanEnts3D: Exploiting Phrase-to-3D-Object Correspondences for Improved Visio-Linguistic Models in 3D Scenes
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2026-03-03 02:55:39
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ScanEnts3D: Exploiting Phrase-to-3D-Object Correspondences for Improved Visio-Linguistic Models in 3D Scenes ScanEnts3D: Exploiting Phrase-to-3D-Object Correspondences for Improved Visio-Linguistic Models in 3D Scenes Ahmed Abdelreheem 1,2 , Kyle Olszewski 2 , Hsin-Ying Lee 2 , Peter Wonka 1 , Panos Achlioptas 2 1 KAUST, 2 Snap Inc. WACV 2024 arXiv Dataset (Released!) Abstract The two popular datasets ScanRefer and ReferIt3D connect natural language to real-world 3D data. In this paper, we curate a large-scale and complementary dataset extending both the aforementioned ones by associating all objects mentioned in a referential sentence to their underlying instances inside a 3D scene. Specifically, our Scan Entities in 3D (ScanEnts3D) dataset provides explicit correspondences between 369k objects, across 84k natural referential sentences, covering 705 real-world scenes. Crucially, we show ...
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