… 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 …

… 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 …

… 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 …

… This study addresses this issue by proposing a view synthesis-based LF image compression
method using a generative adversarial network (GAN). The primary basis of compression …

… compression while image compression is to compress … use a binary generative adversarial
network (BGAN+) to convert images to binary codes for both image retrieval and compression …

… compressed images yielded by yr = ψ(xr,qr), we use roughly the same strategy as that described
in Section 4. In CR-GAN, we replace the compression … along with Gx using the following …

… Compressive sensing magnetic resonance imaging (CSMRI) accelerates the acquisition
of … In this work, a novel generative adversarial network (GAN) based framework for CS-MRI …

… However, existing methods take too much compression time to meet the … data compression
and propose a novel in situ compression method based on generative adversarial network (…

… compression algorithm for parton densities using synthetic replicas generated from the training
of a generative adversarial network (… Carlo PDF set prior to compression. This results in a …