Table 2.
The network architecture of the ResNet generator
Layers | Input | Filter | Stride | Instance | Activation | Output |
---|---|---|---|---|---|---|
size | normalization | function | ||||
Convolution 1 | 256*256*1 | 7*7 | 1 | X | ReLU | 256*256*64 |
Convolution 2 | 256*256*64 | 3*3 | 2 | X | ReLU | 128*128*128 |
Convolution 3 | 128*128*128 | 3*3 | 2 | X | ReLU | 64*64*256 |
Residual Block(RB)x7 | ||||||
Convolution 1 RB | 64*64*256 | 3*3 | 1 | X | ReLU | 64*64*256 |
Convolution 2 RB | 64*64*256 | 3*3 | 1 | X | − | 64*64*256 |
De-Convolution 1 | 64*64*256 | 3*3 | 2 | X | ReLU | 128*128*128 |
De-Convolution 2 | 128*128*128 | 3*3 | 2 | X | ReLU | 256*256*64 |
Convolution 4 | 256*256*64 | 7*7 | 1 | − | tanh | 256*256*1 |