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Unsupervised domain adaptation for clinician pose estimation and instance segmentation in the OR
[article]
2021
The fine-grained localization of clinicians in the operating room (OR) is a key component to design the new generation of OR support systems. Computer vision models for person pixel-based segmentation and body-keypoints detection are needed to better understand the clinical activities and the spatial layout of the OR. This is challenging, not only because OR images are very different from traditional vision datasets, but also because data and annotations are hard to collect and generate in the
doi:10.48550/arxiv.2108.11801
fatcat:sfmrlp46qvbxxbi4guktv7g6pm