Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Idan Kligvasser"'
Autor:
Idan Kligvasser, Tomer Michaeli
Generative adversarial networks (GANs) are known to benefit from regularization or normalization of their critic (discriminator) network during training. In this paper, we analyze the popular spectral normalization scheme, find a significant drawback
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4cd250ff9159f3989626d9516565436
Publikováno v:
CVPR
In recent years, deep neural networks (DNNs) achieved unprecedented performance in many low-level vision tasks. However, state-of-the-art results are typically achieved by very deep networks, which can reach tens of layers with tens of millions of pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd8627d86d157e09dd29c41a8d494e95