Neural Style Transfer and Its Evolution
Neural Style Transfer (NST) is a technique that manipulates digital images to adopt the stylistic elements of another artwork while preserving the original content structure. This is achieved through convolutional neural networks (CNNs) that separate and recombine content and style features. Recent advancements include real-time NST models, such as Fast Neural Style Transfer, which significantly reduces processing time, making the technology more accessible for interactive applications. Modern implementations also support multi-style transfer and adaptive style mixing, enabling greater artistic flexibility.