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What are some examples of procedural generation in video games?
Procedural generation is usually used to create content for video games or animated movies, such as landscapes, 3D objects, character designs, animations, or non-player character dialogue. One famous example of this is the planets generated in “ No Man’s Sky .”
How many nodes are there in material maker?
Nodes are divided into similar categories to Substance Designer, including Generator nodes for creating base patterns, and Filter nodes, for modifying the base pattern into a usable texture. Material Maker’s tool set is still fairly small: in the current release, there are around 20 nodes, compared to the hundreds available in Substance Designer.
How is the generator related to the discriminator?
The counterfeiter (generator) creates increasingly realistic fake bills, and the police (discriminator) become increasingly good at discriminating between real and fake money. Essentially, as the police learn to find the fake bills, the counterfeiter needs to create better-looking bills, resulting in hyper-realistic bills in the long run.
How are neural networks used to generate data?
Neural networks are computer programs that greedily soak up data and learn through what we like to call “osmosis.” In reality, the learning process consists of continually updating small numbers called weights and biases that allow the network to generate data, such as images or likelihood values (e.g., the likelihood that an image is a cat).
How are height maps generated in procedural generation?
To generate our own height maps, we used a Generative Adversarial Network (GAN). GANs consist of a generator network, which generates fake images, and a discriminator network, which discriminates between real images and fake images. This generator-discriminator pair has been compared to a counterfeiter and the police.
How is the learning process used in 3D worlds?
In reality, the learning process consists of continually updating small numbers called weights and biases that allow the network to generate data, such as images or likelihood values (e.g., the likelihood that an image is a cat). To generate 3D worlds, we needed 3D model data and colour data.