We propose a novel frame prediction method using a deep neural network (DNN), with the
goal of improving the video coding efficiency. The proposed DNN makes use of decoded …

Video data have become the main data traffic on the Internet, and their traffic is increasing
explosively every year, thus increasing the pressure of video transmission. Video coding …

We propose a neural network model to estimate the current frame from two reference
frames, using affine transformation and adaptive spatially-varying filters. The estimated …

As online collaborations become more prevalent, screen content has become increasingly
important in real-time video communications. To reduce communication costs, the H …

In this work, we propose a neural network based rate control algorithm for Versatile Video
Coding (VVC). The proposed method relies on the modeling of the Rate-Quantization (RQ) …

In both H. 264/AVC and HEVC, the angular prediction is adopted for intra coding, which only
exploits the spatial correlation between the current block and its neighboring single line …

Rate-distortion (RD) optimization has been widely adopted to improve the coding efficiency
on the video encoder side. However, there are few studies related to modeling the RD …

Rate-control is essential to ensure efficient video delivery. Typical rate-control algorithms
rely on bit allocation strategies, to appropriately distribute bits among frames. As reference …

Inter prediction is a crucial part of hybrid video coding frameworks, utilized to exploit the
temporal redundancy in video sequences and improve the coding performance. During inter …

Abstract The Versatile Video Coding (VVC) has shown significant improvements in Rate-
Distortion (RD) performance compared to its predecessor, High Efficiency Video Coding …