SGR3 Model: Scene Graph Retrieval-Reasoning Model in 3D
3D scene graphs provide a structured representation of object entities and their relationships, enabling high-level interpretation and reasoning for robots while remaining intuitively understandable to humans. Existing approaches for 3D scene graph generation typically combine scene reconstruction with graph neural networks (GNNs). However, such pipelines require multi-modal data that may not always be available, and their reliance on heuristic graph construction can constrain the prediction of relationship triplets. In this work, we introduce a Scene Graph Retrieval-Reasoning Model in 3D (SGR3 Model), a training-free framework that leverages multi-modal large language models (MLLMs) with...
| Authors | Zirui Wang, Ruiping Liu, Yufan Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 4 March 2026 |
| Last updated at source | 4 March 2026 |
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