AI-based upsampling tech creates high-res versions of low-res images

Upsampling image and video files usually leads to pixelation and soft textures, simply because algorithms are not capable of replacing non-existing image detail. But scientists at the Max-Planck Institute for Intelligent Systems in Germany have come up with a clever solution that is capable of producing better results than anything we've seen so far. The team has developed a tool called EnhanceNet-PAT, which is capable of creating high-definition versions of low-resolution images, using artificial intelligence. It's not the first attempt at solving the super-resolution task but the approach is a new one. Talking to Digital Trends, Mehdi M.S. Sajjadi, a member of the research team said "Before this work, even the state of the art has been producing very blurry images, especially at textured regions. The reason for this is that they asked their neural networks the impossible - to reconstruct the original image with pixel-perfect accuracy. Since this is impossible, the neural networks produce blurry results. We take a different approach by instead asking the neural network to produce realistic textures. To do this, the neural network takes a look at the whole image, detects regions, and uses this semantic information to produce realistic textures and sharper images."