Activity Detection in Long Surgical Videos using Spatio-Temporal Models. (arXiv:2205.02805v1 [cs.CV])

Web: http://arxiv.org/abs/2205.02805

Automatic activity detection is an important component for developing
technologies that enable next generation surgical devices and workflow
monitoring systems. In many application, the videos of interest are long and
include several activities; hence, the deep models designed for such purposes
consist of a backbone and a temporal sequence modeling architecture. In this
paper, we investigate both the state-of-the-art activity recognition and
temporal models to find the architectures that yield the highest performance.
We first benchmark these models on a …

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