By optimizing the rate-distortion-realism trade-off, generative compression approaches
produce detailed, realistic images, even at low bit rates, instead of the blurry reconstructions …

In the past years, learned image compression (LIC) has achieved remarkable performance.
The recent LIC methods outperform VVC in both PSNR and MS-SSIM. However, the low bit …

Benefiting from the excellent texture recovery capability of generative adversarial networks
(GANs), generated images are capable of maintaining clear texture features even when …

With the increasing volume of high-resolution satellite images, image compression
technology has become a research hotspot in the field of remote sensing image processing; …

Transferring large amount of high resolution images over limited bandwidth is an important
but very challenging task. Compressing images using extremely low bitrates (< 0.1 bpp) has …

In this paper, we propose a novel image coding framework with semantic-aware visual
decomposition towards extremely low bitrate compression. In particular, an input image is …

Compressing remote sensing images with high spatial and spectral resolution plays an
important role in subsequent image processing and information acquisition. Accurate data …

Recent advances in generative compression methods have demonstrated remarkable
progress in enhancing the perceptual quality of compressed data, especially in scenarios …

Learning-based methods have effectively promoted the community of image compression.
Meanwhile, variational autoencoder (VAE) based variable-rate approaches have recently …

Diffusion probabilistic models have recently achieved remarkable success in generating
high quality image and video data. In this work, we build on this class of generative models …