Spiking neural network, recognized as the third generation of neural networks, has gained significant attention in the research community due to their numerous real-life applications. Convolutional neural networks are renowned for their effectiveness in image processing tasks. Recently, a new variant of the third generation of neural networks has emerged, combining the characteristics of SNNs and CNNs. This variant is known as convolutional spiking neural networks. In this paper, we provide an overview of various ConvSNN models, comparing their properties and examining their advantages and disadvantages. Additionally, we explore the real-life applications of these models.