Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
Image manipulation dates back long before the deep learning era. The classical prevailing approaches were based on maximizing patch similarity between the input and generated output. Recently, single-image GANs were introduced as a superior and more sophisticated solution to image manipulation tasks. Moreover, they offered the opportunity not only to …