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Found 3 papers, 1 papers with code
A self-adapting super-resolution structures framework for automatic design of GAN
In this paper, we introduce a new super-resolution image reconstruction generative adversarial network framework, and a Bayesian optimization method used to optimizing the hyperparameters of the generator and discriminator.
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN
The generator consists of feature extraction and image reconstruction.
Pun-GAN: Generative Adversarial Network for Pun Generation
It consists of a generator to produce pun sentences, and a discriminator to distinguish between the generated pun sentences and the real sentences with specific word senses.
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