  Vastextures is a vast repository of 500,000 textures and PBR materials
extracted from real-world images using an unsupervised process. The extracted
materials and textures are extremely diverse and cover a vast range of
real-world patterns, but at the same time less refined compared to existing
repositories. The repository is composed of 2D textures cropped from natural
images and SVBRDF/PBR materials generated from these textures. Textures and PBR
materials are essential for CGI. Existing materials repositories focus on
games, animation, and arts, that demand a limited amount of high-quality
assets. However, virtual worlds and synthetic data are becoming increasingly
important for training A.I systems for computer vision. This application
demands a huge amount of diverse assets but at the same time less affected by
noisy and unrefined assets. Vastexture aims to address this need by creating a
free, huge, and diverse assets repository that covers as many real-world
materials as possible. The materials are automatically extracted from natural
images in two steps: 1) Automatically scanning a giant amount of images to
identify and crop regions with uniform textures. This is done by splitting the
image into a grid of cells and identifying regions in which all of the cells
share a similar statistical distribution. 2) Extracting the properties of the
PBR material from the cropped texture. This is done by randomly guessing every
correlation between the properties of the texture image and the properties of
the PBR material. The resulting PBR materials exhibit a vast amount of
real-world patterns as well as unexpected emergent properties. Neutral nets
trained on this repository outperformed nets trained using handcrafted assets.
