SAGE-OR: Semi-supervised Adaptive Scene Graph Generation for Operating Rooms

SAGE-OR is a semi‑supervised framework for generating scene graphs in operating rooms that eliminates the need for dense multi‑modal supervision and specialized hardware. It replaces the traditional detect‑then‑reason pipeline with a decoupled representation‑reasoning approach, using frozen foundation models for localization and a lightweight 15‑million‑parameter graph transformer for relational reasoning. On the 4D‑OR benchmark, the core model matches fully supervised baselines (76% F1) and, with unsupervised hand augmentation, reaches 86% F1, achieving near state‑of‑the‑art performance while requiring only relationship and class labels.

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• llms
• computer-vision
• multimodal
• benchmarks