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yunjey · May 10, 2018 · 66783db · 66783db
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 #### Content loss
 
-To minimize the content difference, we forward propagate the content image and the target image to pretrained [VGGNet](https://arxiv.org/abs/1409.1556) respectively, and extract feature maps from multiple convolutional layers. Then, the target image is updated to minimize the [mean-squared error](https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/03-advanced/neural_style_transfer/main.py#L92-L93) between the feature maps of the content image and its feature maps. 
+To minimize the content difference, we forward propagate the content image and the target image to pretrained [VGGNet](https://arxiv.org/abs/1409.1556) respectively, and extract feature maps from multiple convolutional layers. Then, the target image is updated to minimize the [mean-squared error](https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/03-advanced/neural_style_transfer/main.py#L81-L82) between the feature maps of the content image and its feature maps. 
 
 #### Style loss
 
-As in computing the content loss, we forward propagate the style image and the target image to the VGGNet and extract convolutional feature maps. To generate a texture that matches the style of the style image, we update the target image by minimizing the mean-squared error between the Gram matrix of the style image and the Gram matrix of the target image (feature correlation minimization). See [here](https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/03-advanced/neural_style_transfer/main.py#L95-L105) for how to compute the style loss.
+As in computing the content loss, we forward propagate the style image and the target image to the VGGNet and extract convolutional feature maps. To generate a texture that matches the style of the style image, we update the target image by minimizing the mean-squared error between the Gram matrix of the style image and the Gram matrix of the target image (feature correlation minimization). See [here](https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/03-advanced/neural_style_transfer/main.py#L84-L94) for how to compute the style loss.