Generative Adversarial Networks Projects

The architecture of the generator network

The generator network contains five volumetric, fully convolutional layers with the following configuration:

• Convolutional layers: 5
• Filters: 512, 256, 128, 64, 1
• Kernel size: 4 x 4 x 4, 4 x 4 x 4, 4 x 4 x 4, 4 x 4 x 4, 4 x 4 x 4
• Strides: 1, 2, 2, 2, 2 or (1, 1), (2, 2), (2, 2), (2, 2), (2, 2) 
• Batch normalization: Yes, Yes, Yes, Yes, No
• Activations: ReLU, ReLU, ReLU, ReLU, Sigmoid
• Pooling layers: No, No, No, No, No
• Linear layers: No, No, No, No, No

The input and output of the network are as follows:

• Input: A 200-dimensional vector sampled from a probabilistic latent space
• Output: A 3D image with a shape of 64x64x64

 The architecture of the generator can be seen in the following image:

The flow ...