168 citations · 1.8k across the 114 of their papers we have counts for
32 papers · 1 filter
Light Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions
Qiang Qu, Xiaoming Chen, Vera Chung +1
In multimedia broadcasting, no-reference image quality assessment (NR-IQA) is used to indicate the user-perceived quality of experience (QoE) and to support intelligent data transm…
Light Field Compression Based on Implicit Neural Representation
Henan Wang, Hanxin Zhu, Zhibo Chen
Light field, as a new data representation format in multimedia, has the ability to capture both intensity and direction of light rays. However, the additional angular information a…
Exploring the Rate-Distortion-Complexity Optimization in Neural Image Compression
Yixin Gao, Runsen Feng, Zongyu Guo +1
Despite a short history, neural image codecs have been shown to surpass classical image codecs in terms of rate-distortion performance. However, most of them suffer from significan…
Semantically Structured Image Compression via Irregular Group-Based Decoupling
Ruoyu Feng, Yixin Gao, Xin Jin +2
Image compression techniques typically focus on compressing rectangular images for human consumption, however, resulting in transmitting redundant content for downstream applicatio…
Hierarchical Reinforcement Learning Based Video Semantic Coding for Segmentation
Guangqi Xie, Xin Li, Shiqi Lin +4
The rapid development of intelligent tasks, e.g., segmentation, detection, classification, etc, has brought an urgent need for semantic compression, which aims to reduce the compre…
Learning Cross-Scale Weighted Prediction for Efficient Neural Video Compression
Zongyu Guo, Runsen Feng, Zhizheng Zhang +2
Neural video codecs have demonstrated great potential in video transmission and storage applications. Existing neural hybrid video coding approaches rely on optical flow or Gaussia…
Texture-enhanced Light Field Super-resolution with Spatio-Angular Decomposition Kernels
Zexi Hu, Xiaoming Chen, Henry Wing Fung Yeung +2
Despite the recent progress in light field super-resolution (LFSR) achieved by convolutional neural networks, the correlation information of light field (LF) images has not been su…
Versatile Learned Video Compression
Runsen Feng, Zongyu Guo, Zhizheng Zhang +1
Learned video compression methods have demonstrated great promise in catching up with traditional video codecs in their rate-distortion (R-D) performance. However, existing learned…
Task-driven Semantic Coding via Reinforcement Learning
Xin Li, Jun Shi, Zhibo Chen
Task-driven semantic video/image coding has drawn considerable attention with the development of intelligent media applications, such as license plate detection, face detection, an…
Adaptive Hypergraph Convolutional Network for No-Reference 360-degree Image Quality Assessment
Jun Fu, Chen Hou, Wei Zhou +2
In no-reference 360-degree image quality assessment (NR 360IQA), graph convolutional networks (GCNs), which model interactions between viewports through graphs, have achieved impre…
Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalness
Wei Zhou, Zhou Wang, Zhibo Chen
Single image super-resolution (SISR) algorithms reconstruct high-resolution (HR) images with their low-resolution (LR) counterparts. It is desirable to develop image quality assess…
Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng +1
Quantization is one of the core components in lossy image compression. For neural image compression, end-to-end optimization requires differentiable approximations of quantization,…
Learned Block-based Hybrid Image Compression
Yaojun Wu, Xin Li, Zhizheng Zhang +2
Recent works on learned image compression perform encoding and decoding processes in a full-resolution manner, resulting in two problems when deployed for practical applications. F…
Deep Multi-Scale Features Learning for Distorted Image Quality Assessment
Wei Zhou, Zhibo Chen
Image quality assessment (IQA) aims to estimate human perception based image visual quality. Although existing deep neural networks (DNNs) have shown significant effectiveness for…
FAN: Frequency Aggregation Network for Real Image Super-resolution
Yingxue Pang, Xin Li, Xin Jin +4
Single image super-resolution (SISR) aims to recover the high-resolution (HR) image from its low-resolution (LR) input image. With the development of deep learning, SISR has achiev…
Deep Local and Global Spatiotemporal Feature Aggregation for Blind Video Quality Assessment
Wei Zhou, Zhibo Chen
In recent years, deep learning has achieved promising success for multimedia quality assessment, especially for image quality assessment (IQA). However, since there exist more comp…
LIRA: Lifelong Image Restoration from Unknown Blended Distortions
Jianzhao Liu, Jianxin Lin, Xin Li +3
Most existing image restoration networks are designed in a disposable way and catastrophically forget previously learned distortions when trained on a new distortion removal task.…
Residual Squeeze-and-Excitation Network for Fast Image Deraining
Jun Fu, Jianfeng Xu, Kazuyuki Tasaka +1
Image deraining is an important image processing task as rain streaks not only severely degrade the visual quality of images but also significantly affect the performance of high-l…
Multi-scale Grouped Dense Network for VVC Intra Coding
Xin Li, Simeng Sun, Zhizheng Zhang +1
Versatile Video Coding (H.266/VVC) standard achieves better image quality when keeping the same bits than any other conventional image codec, such as BPG, JPEG, and etc. However, i…
Learned Video Compression with Feature-level Residuals
Runsen Feng, Yaojun Wu, Zongyu Guo +3
In this paper, we present an end-to-end video compression network for P-frame challenge on CLIC. We focus on deep neural network (DNN) based video compression, and improve the curr…
3-D Context Entropy Model for Improved Practical Image Compression
Zongyu Guo, Yaojun Wu, Runsen Feng +2
In this paper, we present our image compression framework designed for CLIC 2020 competition. Our method is based on Variational AutoEncoder (VAE) architecture which is strengthene…
Blind Quality Assessment for Image Superresolution Using Deep Two-Stream Convolutional Networks
Wei Zhou, Qiuping Jiang, Yuwang Wang +2
Numerous image superresolution (SR) algorithms have been proposed for reconstructing high-resolution (HR) images from input images with lower spatial resolutions. However, effectiv…
Blind Omnidirectional Image Quality Assessment with Viewport Oriented Graph Convolutional Networks
Jiahua Xu, Wei Zhou, Zhibo Chen
Quality assessment of omnidirectional images has become increasingly urgent due to the rapid growth of virtual reality applications. Different from traditional 2D images and videos…
Generative Memorize-Then-Recall framework for low bit-rate Surveillance Video Compression
Yaojun Wu, Tianyu He, Zhibo Chen
Applications of surveillance video have developed rapidly in recent years to protect public safety and daily life, which often detect and recognize objects in video sequences. Trad…