A team of researchers at Oxford University in the United Kingdom and Skolkovo Institute of Science and Technology in Moscow, capital of the Russian Federation, have developed a neural network technology capable of rendering low-res and corrupted images into clear pictures.
The system, called Deep Image Prior, uses the reverse process of image learning based neural networks. Rather than learn through reviewing tons of related images, Deep Image Prior works within the corrupted or low-res image to shape the contours and sharpen the image using information within only that image. The result is quite impressive, to say the least. Co-author of the research Dmitry Ulyanov explained that the “‘network kind of fills the corrupted regions with textures from nearby.’ Instead of using the data from the datasets, Deep Image Prior redraws a blurry or damager picture until it gets it right. According to Interesting Engineering, some images turn out to be even better than the original input.”