论文标题
基于视觉的预测深度学习：一项调查
Deep Learning for Vision-based Prediction: A Survey
论文作者
论文摘要
基于视觉的预测算法具有广泛的应用，包括自主驾驶，监视，人类机器人相互作用，天气预测。本文的目的是在过去五年中概述该领域，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，我们强调所使用的数据的共同体系结构，培训方法和类型。此外，我们讨论用于基于视觉预测任务的常见评估指标和数据集。可以在https://github.com/Aras62/vision基于基础上的基础上找到本调查中所有信息的数据库，包括根据论文，数据集和指标进行的交叉引用。
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.
