Introduction: Syle Transfer with GANs
Explore how generative adversarial networks (GANs) enable style transfer by transforming images to emulate artistic styles. Understand paired and unpaired image-to-image style transfer methods, study key GAN architectures, and gain practical experience by building and training models from scratch to deepen your understanding of creative AI techniques.
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Neural networks are improving in a number of tasks involving analytical and linguistic skills. Creativity is one sphere where humans have had the upper hand. Not only is art subjective and has no defined boundaries, but it is also difficult to quantify. Yet, this has not stopped researchers from exploring the creative capabilities of algorithms. Over the years, there have been several successful attempts at creating, understanding, and even copying art or artistic styles, a few examples being ...