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Encoder
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Decoder
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Discriminator (Xu’Net)
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|---|
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Input:6×256×256
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Input:3×256×256
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Input:3×256×256
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Conv(6, 64, 7)
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Conv(64,128,3)
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Conv(128,256,3)
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Res_block1(256,256,3)
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Conv(3, 64,3)
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kv_filter(3,1,5)
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Res_block2(256,256,3)
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Conv(64, 128,3)
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Conv(1, 8, 5)
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Res_block3(256,256,3)
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Conv(128,256,3)
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Conv(8, 16, 5)
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Res_block4(256,256,3)
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Conv(256,128,3)
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Conv(16, 32, 3)
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Res_block5(256,256,3)
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Conv(128, 64, 3)
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Conv(32, 64,3)
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Res_block6(256,256,3)
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Conv(64, 3,3)
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Conv(64,128,3)
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Res_block7(256,256,3)
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Sigmoid(3, 3)
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Sigmoid(128,1)
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Res_block8(256,256,3)
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Res_block9(256,256,3)
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DeConv(256,128, 3)
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DeConv(128, 64, 3)
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Conv(64, 3, 7)
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Tanh(3,3)
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Output:3×256×256
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Output:3×256×256
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Output:1
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- Each resnet block includes two 3×3 convolutional layers with batch normalization operation and ReLU activation function, which outputs the result of adding the input feature map and the feature map after two convolutional layers
