You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy 
Chapter Title:  Deep Convolutional GAN (DCGAN) 
1. Abstract of Cited Paper (BIB001):  In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications. Comparatively, unsupervised learning with CNNs has received less attention. In this work we hope to help bridge the gap between the success of CNNs for supervised learning and unsupervised learning. We introduce a class of CNNs called deep convolutional generative adversarial networks (DCGANs), that have certain architectural constraints, and demonstrate that they are a strong candidate for unsupervised learning. Training on various image datasets, we show convincing evidence that our deep convolutional adversarial pair learns a hierarchy of representations from object parts to scenes in both the generator and discriminator. Additionally, we use the learned features for novel tasks - demonstrating their applicability as general image representations.

Literature Review:
DCGAN is the first work that applied a deconvolutional neural networks architecture for G BIB002 . Figure. 4 illustrates the proposed architecture for G. Deconvolution is proposed to visualize the features for a CNN and has shown good performance for CNNs visualization BIB001 . DCGAN deploys the spatial up-sampling ability of the deconvolution operation for G, which enables the generation of higher resolution images using GANs.