Neural Style Transfer: A Critical Review

Neural Style Transfer (NST) is a class of software algorithms that allows us to transform scenes, change/edit the environment media with help Network. NST finds use in image and video editing allowing stylization based on general model, unlike traditional methods. This made trending topic entertainment industry as professional editors/media producers create faster offer public recreational use. In this paper, current progress all related aspects such still images videos presented critically. The authors looked at different architectures used compared their advantages limitations. Multiple literature reviews focus cover Generative Adversarial Networks (GANs) generate video. As per authors’ knowledge, only research article looks style transfer, particularly mobile devices high potential usage. also reviewed challenges faced applying for neural transfer real-time presents gaps future directions. NST, fascinating deep learning application, has considerable application coming years.