Editing Images With Cyclegans
GANs represent the state of the art in image-to-image translation. However, it can be difficult to acquire aligned image pairs to learn the mapping between image domains. CycleGANs introduced the “cycle consistency” constraint to learn to transfigure images, transfer style, and enhance photos from unaligned source and target domain samples. This technique has been used to render historic black & white images in full color or to represent an image in greater resolution but here, we explore applications in agriculture....