Researchers at Nvidia have created a new generative adversarial network model for producing realistic landscape images from a rough sketch or segmentation map, and while it's not perfect, it is certainly a step towards allowing people to create their own synthetic scenery. The GauGAN model is initially being touted as a tool to help urban planners, game designers, and architects quickly create synthetic images. The model was trained on over a million images, including 41,000 from Flickr, with researchers stating it acts as a "smart paintbrush" as it fills in the details on the sketch. "It's like a colouring book picture that describes where a tree is, where the sun is, where the sky is," Nvidia vice president of applied deep learning research Bryan Catanzaro said. "And then the neural network is able to fill in all of the detail and texture, and the reflections, shadows and colours, based on what it has learned about real images."
Mar-19-2019, 03:18:42 GMT