Feb. 13, 2024, 5:47 a.m. | Long Bai Guankun Wang Jie Wang Xiaoxiao Yang Huxin Gao Xin Liang An Wang Mobarakol Islam

cs.CV updates on arXiv.org arxiv.org

In the realm of automated robotic surgery and computer-assisted interventions, understanding robotic surgical activities stands paramount. Existing algorithms dedicated to surgical activity recognition predominantly cater to pre-defined closed-set paradigms, ignoring the challenges of real-world open-set scenarios. Such algorithms often falter in the presence of test samples originating from classes unseen during training phases. To tackle this problem, we introduce an innovative Open-Set Surgical Activity Recognition (OSSAR) framework. Our solution leverages the hyperspherical reciprocal point strategy to enhance the distinction between …

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