OR-Action: Multi-Role Video Understanding with Fine-Grained Actions
Fine-grained understanding of operating room (OR) activity could enable workflow-aware assistance, yet remains difficult due to clutter, occlusions, and limited sensing. The prevailing approach to model this environment is scene graphs as an interpretable representation of OR interactions. Converting their frame-wise relational predictions into temporally extended, fine-grained actions however, is challenging without explicit temporal modeling. To enable a principled temporal evaluation of current OR understanding methods, we introduce the first action-centric benchmark built on a publicly available ego-exocentric OR dataset by defining a fine-grained, multi-role action taxonomy and gener...
| Authors | Felix Tristram, Ege Özsoy, Christian Benz et al. |
|---|---|
| Primary category | cs.CV |
| Published | 11 June 2026 |
| Last updated at source | 11 June 2026 |
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