Improving Neural Style Transfer by Incorporating Mid-Level Representation
Author:
Affiliation:
1. Universidad Católica San Pablo,Dept. of Computer Science,Arequipa,Peru
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9769800/9769778/09769780.pdf?arnumber=9769780
Reference28 articles.
1. Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis
2. Perceptual losses for real-time style transfer and super-resolution;johnson;European Conference on Computer Vision,2016
3. Texture networks: Feed-forward synthesis of textures and stylized images;ulyanov;ICML,2016
4. Improved Texture Networks: Maximizing Quality and Diversity in Feed-Forward Stylization and Texture Synthesis
5. Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
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