Lossy image compression is generally formulated as a joint rate-distortion optimization
problem to learn encoder, quantizer, and decoder. Due to the non-differentiable quantizer …

In this paper, we design a Deep Dual-Domain (D3) based fast restoration model to remove
artifacts of JPEG compressed images. It leverages the large learning capacity of deep …

We propose a highly accurate approach to remove artifacts of JPEG-compressed images.
Our approach jointly learns a very deep convolutional network in both DCT and pixel …

Image restoration is a long-standing problem in image processing and low-level computer
vision. Recently, discriminative convolutional neural network (CNN)-based approaches …

We consider the compression artifacts reduction problem, where a compressed image is
transformed into an artifact-free image. Recent approaches for this problem typically train a …

Lossy compression introduces complex compression artifacts, particularly blocking artifacts,
ringing effects and blurring. Existing algorithms either focus on removing blocking artifacts …

Geometry-based point cloud compression (G-PCC) can achieve remarkable compression
efficiency for point clouds. However, it still leads to serious attribute compression artifacts …

The amount of multimedia data, such as images and videos, has been increasing rapidly
with the development of various imaging devices and the Internet, bringing more stress and …

Color demosaicing is a key image processing step aiming to reconstruct the missing pixels
from a recorded raw image. On the one hand, numerous interpolation methods focusing on …

A motion blurred image stored in the joint photographic experts group (JPEG) image
compression format contains both motion blur and JPEG artifacts. Therefore, it is very difficult …