  Vision-based prediction algorithms have a wide range of applications
including autonomous driving, surveillance, human-robot interaction, weather
prediction. The objective of this paper is to provide an overview of the field
in the past five years with a particular focus on deep learning approaches. For
this purpose, we categorize these algorithms into video prediction, action
prediction, trajectory prediction, body motion prediction, and other prediction
applications. For each category, we highlight the common architectures,
training methods and types of data used. In addition, we discuss the common
evaluation metrics and datasets used for vision-based prediction tasks. A
database of all the information presented in this survey including,
cross-referenced according to papers, datasets and metrics, can be found online
at https://github.com/aras62/vision-based-prediction.
