GANcraft: Turning Gamers into 3D Artists
GANcraft: Turning Gamers into 3D Artists | NVIDIA Developer Blog
“Scientists at NVIDIA and Cornell University introduced a hybrid unsupervised neural rendering pipeline to represent large and complex scenes efficiently in voxel worlds. Essentially, a 3D artist only needs to build the bare minimum, and the algorithm will do the rest to build a photorealistic world. The researchers applied this hybrid neural rendering pipeline to Minecraft block worlds to generate a far more realistic version of the Minecraft scenery.
Previous works from NVIDIA and the broader research community (pix2pix, pix2pixHD, MUNIT, SPADE) have tackled the problem of image-to-image translation (im2im)—translating an image from one domain to another. At first glance, these methods might seem to offer a simple solution to the task of transforming one world to another—translating one image at a time. However, im2im methods do not preserve viewpoint consistency, as they have no knowledge of the 3D geometry, and each 2D frame is generated independently. As can be seen in the images that follow, the results from these methods produce jitter and abrupt color and texture changes…”