image to image

Image-to-image refers to the task of translating an input image into a corresponding output image, typically using a deep learning model. This can involve a variety of tasks, such as image colorization, style transfer, super-resolution, and semantic segmentation. The goal is to learn a mapping between the input and output images in an unsupervised or supervised manner, depending on the availability of labeled training data. Image-to-image models have a wide range of applications in computer vision, including enhancing image quality, generating realistic images, and enabling new forms of image manipulation.