39 citations · 59 across the 13 of their papers we have counts for
10 papers · 1 filter
Fast QTMT Partition for VVC Intra Coding Using U-Net Framework
Zhao Zan, Leilei Huang, ShuShi Chen +4
Versatile Video Coding (VVC) has significantly increased encoding efficiency at the expense of numerous complex coding tools, particularly the flexible Quad-Tree plus Multi-type Tr…
An Error-Surface-Based Fractional Motion Estimation Algorithm and Hardware Implementation for VVC
Shushi Chen, Leilei Huang, Jiahao Liu +2
Versatile Video Coding (VVC) introduces more coding tools to improve compression efficiency compared to its predecessor High Efficiency Video Coding (HEVC). For inter-frame coding,…
FAVER: Blind Quality Prediction of Variable Frame Rate Videos
Qi Zheng, Zhengzhong Tu, Pavan C. Madhusudana +3
Video quality assessment (VQA) remains an important and challenging problem that affects many applications at the widest scales. Recent advances in mobile devices and cloud computi…
Learned Video Compression with Residual Prediction and Loop Filter
Chao Liu, Heming Sun, Jiro Katto +2
In this paper, we propose a learned video codec with a residual prediction network (RP-Net) and a feature-aided loop filter (LF-Net). For the RP-Net, we exploit the residual of pre…
CSMCNet: Scalable Video Compressive Sensing Reconstruction with Interpretable Motion Estimation
Bowen Huang, Xiao Yan, Jinjia Zhou +1
Most deep network methods for compressive sensing reconstruction suffer from the black-box characteristic of DNN. In this paper, a deep neural network with interpretable motion est…
Image Compression with Encoder-Decoder Matched Semantic Segmentation
Trinh Man Hoang, Jinjia Zhou, Yibo Fan
In recent years, layered image compression is demonstrated to be a promising direction, which encodes a compact representation of the input image and apply an up-sampling network t…
A QP-adaptive Mechanism for CNN-based Filter in Video Coding
Chao Liu, Heming Sun, Jiro Katto +2
Convolutional neural network (CNN)-based filters have achieved great success in video coding. However, in most previous works, individual models are needed for each quantization pa…
CS-MCNet:A Video Compressive Sensing Reconstruction Network with Interpretable Motion Compensation
Bowen Huang, Jinjia Zhou, Xiao Yan +3
In this paper, a deep neural network with interpretable motion compensation called CS-MCNet is proposed to realize high-quality and real-time decoding of video compressive sensing.…
A Convolutional Neural Network-Based Low Complexity Filter
Chao Liu, Heming Sun, Jiro Katto +2
Convolutional Neural Network (CNN)-based filters have achieved significant performance in video artifacts reduction. However, the high complexity of existing methods makes it diffi…
Dual Learning-based Video Coding with Inception Dense Blocks
Chao Liu, Heming Sun, Junan Chen +5
In this paper, a dual learning-based method in intra coding is introduced for PCS Grand Challenge. This method is mainly composed of two parts: intra prediction and reconstruction…