a.取消所有pooling层。G网络中使用转置卷积(transposed convolutional layer)进行上采样,D网络中用加入stride的卷积代替pooling。 b.在D和G中均使用batch normalization c.去掉FC层,使网络变为全卷积网络 d.G网络中使用ReLU作为激活函数,最后一层使用tanh e.D网络中使用LeakyReLU作为激活函数 DCGAN
> 论文主页:https://phillipi.github.io/pix2pix/,其中包含了PyTorch、Tensorflow等主流框架的代码实现 图像、视觉中很多问题都涉及到将一副图像转换为另一幅图像(Image-to-Image Translation Problem),这些问题通常都使用特定的方法来解决,不存在一个通用的方法。但图像转换问题本质上其实就是像素到像素的映射问题,...
此类方法能够处理不同的模糊源。 Figure 3: DeblurGAN generator architecture. DeblurGAN contains two strided convolution blocks with stride 1/2, nine residual blocks [13] and two transposed convolution blocks. Each ResBlock consists of a convolution layer, instance normalization layer, and ReLU activatio...
此类方法能够处理不同的模糊源。 Figure 3: DeblurGAN generator architecture. DeblurGAN contains two strided convolution blocks with stride 1/2, nine residual blocks [13] and two transposed convolution blocks. Each ResBlock consists of a convolution layer, instance normalization layer, and ReLU activatio...
Figure 3: DeblurGAN generator architecture. DeblurGAN contains two strided convolution blocks with stride 1/2, nine residual blocks [13] and two transposed convolution blocks. Each ResBlock consists of a convolution layer, instance normalization layer, and ReLU activation. ...