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RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding
May 7, 2024, 4:48 a.m. | Jihan Yang, Runyu Ding, Weipeng Deng, Zhe Wang, Xiaojuan Qi
cs.CV updates on arXiv.org arxiv.org
Abstract: We propose a lightweight and scalable Regional Point-Language Contrastive learning framework, namely \textbf{RegionPLC}, for open-world 3D scene understanding, aiming to identify and recognize open-set objects and categories. Specifically, based on our empirical studies, we introduce a 3D-aware SFusion strategy that fuses 3D vision-language pairs derived from multiple 2D foundation models, yielding high-quality, dense region-level language descriptions without human 3D annotations. Subsequently, we devise a region-aware point-discriminative contrastive learning objective to enable robust and effective 3D …
arxiv cs.ai cs.cv language open-world regional type understanding world
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