Convolutional Generative Neural Networks (CGNNs) present as a powerful class of deep learning architectures for generating synthetic data. CGNNs combine the strengths of convolutional neural networks renowned for their ability to learn spatial features with generative models, which are designed to produce novel data instances. This survey provides