On the Layer Choice of the Image Style Transfer Using Convolutional Neural Networks
In this paper, the layer choices of the image style transfer method using the VGG 19 neural network are studied. The VGG 19 network is used to extract the feature maps which have their implicit meaning as a learning basis. If the layers for stylistic learning are not suitably chosen, the quality of style transferred image may not look good. After making experiments, it can be observed that the color information is concentrated on lower layers from conv1 1 to conv2 2, and texture information is concentrated on the middle layers from conv3 1 to conv4 4. As to the higher layers from conv5 1 to conv5 4, they seem to be able to depict image content well. Based on these observations, the methods of color transfer, texture transfer and style transfer are presented and make comparisons with conventional methods.
2019 IEEE International Conference on Consumer Electronics Taiwan (ICCE TW)