Iterative weak/self-supervised classification framework for abnormal events detection

This paper introduces one iterative learning framework composed of two experts working in the weak and self-supervised paradigms and providing additional amounts of learning data to each other, where the novel instances at each iteration are edited by a Bayesian framework that supports the iterative data augmentation task.