Image Scene Transformation Based on Dynamic Mutual Information Generative Adversarial Networks
Author:
Affiliation:
1. Liaoning Technical University,Software College,Huludao,Liaoning,China,125105
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10176329/10176364/10176457.pdf?arnumber=10176457
Reference19 articles.
1. Wasserstein GAN[J];arjovsky,2017
2. StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation
3. Which Training Methods for GANs do actually Converge?[J];mescheder,2018
4. Wasserstein Divergence for GANs[J];wu,2017
5. Progressive Growing of GANs for Improved Quality, Stability, and Variation[J];karras,2017
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