A spatiotemporal deep learning framework for detecting unusual human activity in surveillance videos
A transfer learning-based hybrid deep framework for finding unusual activity in real-world surveillance that performs better than the state of art methods and identifies abnormal actions of human beings in challenging monitoring situations is proposed.