Image Difficulty Curriculum for Generative Adversarial Networks (CuGAN)

Despite the significant advances in recent years, Generative Adversarial Networks (GANs) are still notoriously hard to train. In this paper, we propose three novel curriculum learning strategies for training GANs. All strategies are first based on ranking the training images by their difficulty scor...

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Veröffentlicht in:	arXiv.org 2019-10
Hauptverfasser:	Soviany, Petru, Ardei, Claudiu, Radu Tudor Ionescu, Leordeanu, Marius
Format:	Artikel
Sprache:	eng
Schlagworte:	Convergence Curricula Generative adversarial networks Image processing Strategy Training
Online-Zugang:	Volltext
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