Cutout with patch-loss augmentation for improving generative adversarial networks against instability-Reference-Cited by-同舟云学术

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Cutout with patch-loss augmentation for improving generative adversarial networks against instability

Published:2023-09 Issue: Volume:234 Page:103761
ISSN:1077-3142
Container-title:Computer Vision and Image Understanding
language:en
Short-container-title:Computer Vision and Image Understanding

Author:

Shi Mengchen^ORCID,Xie Fei,Yang Jiquan,Zhao Jing,Liu Xixiang,Wang Fan

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference44 articles.

1. Towards principled methods for training generative adversarial networks;Arjovsky,2017

2. Wasserstein GAN;Arjovsky,2017

3. Learning with pseudo-ensembles;Bachman,2014

4. Large scale GAN training for high fidelity natural image synthesis;Brock,2018

5. Large scale GAN training for high fidelity natural image synthesis;Brock,2019

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