arXiv:2512.23020v3 Announce Type: replace-cross Abstract: 3D visual grounding aims to locate objects based on natural language descriptions in 3D scenes. Existing supervised methods are limited by generalization and recent zero-shot methods typically rely on a predefined Object Lookup Table (OLT) to query Visual Language Models (VLMs) for reasoning about object locations via a single step grounding, which limits the applications in scenarios with undefined targets and complex queries. To address these problems, we present OpenGround, a novel zero-shot framework for open-world 3D visual groundi
This development appears now as research seeks to overcome limitations in existing 3D visual grounding methods, particularly regarding generalization and open-world applications for AI systems.
Advanced 3D visual grounding is crucial for AI systems to interact more intelligently and robustly in real-world environments, enabling finer control and understanding.
This research suggests a more robust and flexible approach to 3D visual grounding, moving beyond predefined object lists and single-step reasoning, enhancing AI's open-world capabilities.
- · AI developers
- · Robotics industry
- · Computer vision researchers
- · Logistics and manufacturing
- · Companies relying on limited, supervised 3D grounding systems
AI systems will become more adept at identifying and interacting with novel objects in complex 3D environments.
This improved perception could accelerate the development and deployment of autonomous robots and augmented reality applications.
Enhanced open-world 3D understanding might lead to entirely new human-computer interaction paradigms and increased autonomy in various sectors.
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Read at arXiv cs.AI