Optimizing Latent Distributions for Non-Adversarial Generative Networks

IEEE Transactions on Pattern Analysis and Machine Intelligence(2022)

引用 26|浏览116
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摘要
The generator in generative adversarial networks (GANs) is driven by a discriminator to produce high-quality images through an adversarial game. At the same time, the difficulty of reaching a stable generator has been increased. This paper focuses on non-adversarial generative networks that are trained in a plain manner without adversarial loss. The given limited number of real images could be ins...
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关键词
Training,Generators,Gallium nitride,Optimization,Image reconstruction,Linear programming,Generative adversarial networks
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