English

Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs

Robotics 2023-09-29 v1 Computer Vision and Pattern Recognition

Abstract

We present an Open-Vocabulary 3D Scene Graph (OVSG), a formal framework for grounding a variety of entities, such as object instances, agents, and regions, with free-form text-based queries. Unlike conventional semantic-based object localization approaches, our system facilitates context-aware entity localization, allowing for queries such as ``pick up a cup on a kitchen table" or ``navigate to a sofa on which someone is sitting". In contrast to existing research on 3D scene graphs, OVSG supports free-form text input and open-vocabulary querying. Through a series of comparative experiments using the ScanNet dataset and a self-collected dataset, we demonstrate that our proposed approach significantly surpasses the performance of previous semantic-based localization techniques. Moreover, we highlight the practical application of OVSG in real-world robot navigation and manipulation experiments.

Keywords

Cite

@article{arxiv.2309.15940,
  title  = {Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs},
  author = {Haonan Chang and Kowndinya Boyalakuntla and Shiyang Lu and Siwei Cai and Eric Jing and Shreesh Keskar and Shijie Geng and Adeeb Abbas and Lifeng Zhou and Kostas Bekris and Abdeslam Boularias},
  journal= {arXiv preprint arXiv:2309.15940},
  year   = {2023}
}

Comments

The code and dataset used for evaluation can be found at https://github.com/changhaonan/OVSG}{https://github.com/changhaonan/OVSG. This paper has been accepted by CoRL2023

R2 v1 2026-06-28T12:34:12.973Z