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.

中文翻译：

---

基于视觉的预测的深度学习：一项调查

基于视觉的预测算法具有广泛的应用，包括自动驾驶、监控、人机交互、天气预报。本文的目的是提供过去五年该领域的概述，特别关注深度学习方法。为此，我们将这些算法分为视频预测、动作预测、轨迹预测、身体运动预测和其他预测应用。对于每个类别，我们重点介绍了常用的架构、训练方法和使用的数据类型。此外，我们讨论了用于基于视觉的预测任务的常见评估指标和数据集。本次调查中提供的所有信息的数据库，包括根据论文、数据集和指标的交叉引用，可以在 https://github 在线找到。