Zeus: Efficiently Localizing Actions in Videos using Reinforcement Learning
Pramod Chunduri, Jaeho Bang, Yao Lu, Joy James Prabhu Arulraj · Proceedings of the 2022 International Conference on Management of Data · 2022
Detection and localization of actions in videos is an important problem in practice. State-of-the-art video analytics systems are unable to efficiently and effectively answer such action queries because actions often involve a complex interaction between objects and are spread across a sequence of frames; detecting and localizing them requires computationally expensive deep neural networks. It is also important to consider the entire sequence of frames to answer the query effectively.