… trained for compression of general natural images are preferred to BPG when BPG uses up
… our GC models are preferred to BPG even when the latter uses up to 181% more bits. To the …

… The compression of Generative Adversarial Networks (GANs… Existing GAN compression
algorithms are limited to handling … compression, we introduce AutoML to GAN compression and …

… compression framework that uses generative adversarial networks (GAN) to compress …
After completing Stage one, we perform signal compression on the training set images through …

… In this paper, we propose a self-supervised compression technique for generative adversarial
networks and prove its effectiveness across various typical and complex tasks. We also …

… Abstract—We propose a GAN-based image compression method working at extremely low
… pixel (bpp) compression. We propose a novel GAN-based image compression method that …

… More recently, unsupervised generative models based on neural networks have been … In
this paper, we use Generative Adversarial Networks (GANs) to impose structure in compressed …

… In this paper, we use a deep learning-based approach for image compression artifacts …
efficient generative adversarial network (GAN) for this task. We denote the proposed networks as …

… traces left by JPEG compression, we propose an anti-forensic framework of JPEG compression,
using a generative adversarial network (GAN) [7]. GAN is comprised of two networks: a …

… In this paper, we present a LF image compression framework driven by a generative
adversarial network (GAN)-based sub-aperture image (SAI) generation and a cascaded …

… In addition, state-of-the-art compressed sensing (CS) analytics are not cognizant of the … CS
framework that permeates benefits from generative adversarial networks (GAN) to train a (low-…