Hybird Voxel-conditional Neural Rendering This can be trained using predicted images from a im2im method ( pseudo-ground truth, explained in the next section), which is the data closest to the requirements that we can get. These models have to be trained on translating real segmentation maps to real images due to paired training data requirements, and then used on Minecraft to real translation.Īs yet another alternative, one can train a NeRF-W, which learns a 3D radiance field from a non-photometric consistent, but posed and 3D consistent image collection. One can also use wc-vid2vid, a 3D-aware method, to generate view-consistent images through 2D inpainting and 3D warping while using the voxel surfaces as the 3D geometry. For example, one can use image-to-image translation (im2im) methods such as MUNIT and SPADE, originally trained on 2D data only, to convert per-frame segmentation masks projected from the block world, to realistic looking images. Some existing approaches are strong candidates. The " Why don't you just use im2im translation? " QuestionĪs the ground truth photorealistic renderings for a user-created block world simply doesn't exist, we have to train models with indirect supervision.
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