The paper proposes a novel frame-wise filtering method based on Convolutional Neural
Networks (CNNs) for enhancing the quality of HEVC decoded videos. A novel deep neural …

Deep convolutional neural networks (CNNs) have achieved impressive success in
enhancing the quality of compressed images/videos. These approaches mostly obtain the …

Video Enhancement is an important computer vision task aiming at the removal of the
artifacts from a lossy compressed video and the improvement of the visual properties by a …

Many convolutional neural network (CNN)-based in-loop filters have been proposed to
improve coding performance. However, considering the single perception scale, high …

Advanced video codecs such as High Efficiency Video Coding/H. 265 (HEVC) and Versatile
Video Coding/H. 266 (VVC) are vital for streaming high-quality online video content, as they …

Many studies have focused on utilizing convolutional neural networks (CNNs) to enhance
loop filter performance in video encoding. However, existing methods primarily concentrate …

The rapid development of 3D modeling and computer vision has made point cloud data
essential across various industries. Effective processing, transmission, and storage of these …

The past decade has witnessed fast development in multiview 3D video technologies, such
as Three-Dimensional Video (3DV), Virtual Reality (VR), and Free Viewpoint Video (FVV) …

With the great success of deep learning network, compressed video quality enhancement
methods based on deep learning are mushrooming. Most of these methods ignore the …

This paper presents a novel optimized quantization constraint set, acting as an add-on to
existing DCT-based image restoration algorithms. The constraint set is created based on …