158 citations · 491 across the 20 of their papers we have counts for
13 papers · 1 filter
Sub-sampled Cross-component Prediction for Emerging Video Coding Standards
Junru Li, Meng Wang, Li Zhang +5
Cross-component linear model (CCLM) prediction has been repeatedly proven to be effective in reducing the inter-channel redundancies in video compression. Essentially speaking, the…
Unpaired Image Enhancement with Quality-Attention Generative Adversarial Network
Zhangkai Ni, Wenhan Yang, Shiqi Wang +2
In this work, we aim to learn an unpaired image enhancement model, which can enrich low-quality images with the characteristics of high-quality images provided by users. We propose…
Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network
Zhangkai Ni, Wenhan Yang, Shiqi Wang +2
Improving the aesthetic quality of images is challenging and eager for the public. To address this problem, most existing algorithms are based on supervised learning methods to lea…
Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment
Baoliang Chen, Lingyu Zhu, Guo Li +2
In this work, we propose a no-reference video quality assessment method, aiming to achieve high-generalization capability in cross-content, -resolution and -frame rate quality pred…
Conceptual Compression via Deep Structure and Texture Synthesis
Jianhui Chang, Zhenghui Zhao, Chuanmin Jia +5
Existing compression methods typically focus on the removal of signal-level redundancies, while the potential and versatility of decomposing visual data into compact conceptual com…
Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization
Haoliang Li, YuFei Wang, Renjie Wan +3
Recently, we have witnessed great progress in the field of medical imaging classification by adopting deep neural networks. However, the recent advanced models still require access…
DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing
Rizhao Cai, Haoliang Li, Shiqi Wang +2
Inspired by the philosophy employed by human beings to determine whether a presented face example is genuine or not, i.e., to glance at the example globally first and then carefull…
Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems
Haoliang Li, Yufei Wang, Xiaofei Xie +5
Deep neural networks (DNN) have shown great success in many computer vision applications. However, they are also known to be susceptible to backdoor attacks. When conducting backdo…
High Efficiency Rate Control for Versatile Video Coding Based on Composite Cauchy Distribution
Yunhao Mao, Meng Wang, Shiqi Wang +1
In this work, we propose a novel rate control algorithm for Versatile Video Coding (VVC) standard based on its distinct rate-distortion characteristics. By modelling the transform…
Towards Modality Transferable Visual Information Representation with Optimal Model Compression
Rongqun Lin, Linwei Zhu, Shiqi Wang +1
Compactly representing the visual signals is of fundamental importance in various image/video-centered applications. Although numerous approaches were developed for improving the i…
No-reference Screen Content Image Quality Assessment with Unsupervised Domain Adaptation
Baoliang Chen, Haoliang Li, Hongfei Fan +1
In this paper, we quest the capability of transferring the quality of natural scene images to the images that are not acquired by optical cameras (e.g., screen content images, SCIs…
User-generated Video Quality Assessment: A Subjective and Objective Study
Yang Li, Shengbin Meng, Xinfeng Zhang +3
Recently, we have observed an exponential increase of user-generated content (UGC) videos. The distinguished characteristic of UGC videos originates from the video production and d…
Iterative Network for Image Super-Resolution
Yuqing Liu, Shiqi Wang, Jian Zhang +3
Single image super-resolution (SISR), as a traditional ill-conditioned inverse problem, has been greatly revitalized by the recent development of convolutional neural networks (CNN…