DCGAN, or Deep Convolutional GAN, is a generative adversarial network architecture. It uses a couple of guidelines, in particular:
Paper | Code | Results | Date | Stars |
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Task | Papers | Share |
---|---|---|
Image Generation | 22 | 25.29% |
Translation | 5 | 5.75% |
Conditional Image Generation | 3 | 3.45% |
Image-to-Image Translation | 2 | 2.30% |
Anomaly Detection | 2 | 2.30% |
Decoder | 2 | 2.30% |
Medical Image Generation | 2 | 2.30% |
Object Detection | 2 | 2.30% |
Pedestrian Detection | 2 | 2.30% |
Component | Type |
|
---|---|---|
Batch Normalization
|
Normalization | |
Convolution
|
Convolutions | |
Leaky ReLU
|
Activation Functions | |
ReLU
|
Activation Functions |