Evolutionary algorithms (EAs) and swarm algorithms (SAs) have shown their usefulness in solving combinatorial and NP-hard optimization problems in various research fields. However, in the field of computer vision, related surveys have not been updated during the last decade. In this study, inspired by the recent development of deep neural networks in computer vision, which embed large-scale optimization problems, we first describe a literature survey conducted to compensate for the lack of relevant research in this area. Specifically, applications related to the genetic algorithm and differential evolution from EAs, as well as particle swarm optimization and ant colony optimization from SAs and their variants, are mainly considered in this survey.

中文翻译：

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进化和群体优化在计算机视觉中的应用：文献综述

进化算法（EA）和群体算法（SA）已显示出它们在解决各种研究领域中的组合和NP困难优化问题方面的有用性。但是，在计算机视觉领域，相关调查在过去十年中没有更新。在这项研究中，受计算机视觉中深度神经网络的最新发展的启发，该网络中嵌入了大规模的优化问题，我们首先描述为弥补这一领域相关研究不足而进行的文献调查。具体而言，本调查主要考虑与遗传算法和EA的差分进化有关的应用，以及与SA及其变体有关的粒子群优化和蚁群优化。