January 2019
Intermediate to advanced
316 pages
8h 16m
English
3D Generative Adversarial Networks (3D-GANs) is a variant of GANs, just like StackGANs, CycleGANs, and Super-Resolution Generative Adversarial Networks (SRGANs). Similar to a vanilla GAN, it has a generator and a discriminator model. Both of the networks use 3D convolutional layers, instead of using 2D convolutions. If provided with enough data, it can learn to generate 3D shapes with good visual quality.
Let's understand 3D convolutions before looking closer at the 3D-GAN network.
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