activity
20202024
most citedTowards Unsupervised Deep Image Enhancement with Generative Adversarial Network

158 citations · 491 across the 20 of their papers we have counts for

collaborators

20 papers

cs.CV2024

When Video Coding Meets Multimodal Large Language Models: A Unified Paradigm for Video Coding

Pingping Zhang, Jinlong Li, Kecheng Chen +6

Existing codecs are designed to eliminate intrinsic redundancies to create a compact representation for compression. However, strong external priors from Multimodal Large Language…

cs.CV2022★ 3 cited

Just Noticeable Difference Modeling for Face Recognition System

Yu Tian, Zhangkai Ni, Baoliang Chen +4

High-quality face images are required to guarantee the stability and reliability of automatic face recognition (FR) systems in surveillance and security scenarios. However, a massi…

eess.IV2022★ 32 cited

DeepWSD: Projecting Degradations in Perceptual Space to Wasserstein Distance in Deep Feature Space

Xingran Liao, Baoliang Chen, Hanwei Zhu +3

Existing deep learning-based full-reference IQA (FR-IQA) models usually predict the image quality in a deterministic way by explicitly comparing the features, gauging how severely…

cs.IR2022★ 2 cited

Who Are the Best Adopters? User Selection Model for Free Trial Item Promotion

Shiqi Wang, Chongming Gao, Min Gao +3

With the increasingly fierce market competition, offering a free trial has become a potent stimuli strategy to promote products and attract users. By providing users with opportuni…

cs.CV2021★ 2 cited

End-to-end Compression Towards Machine Vision: Network Architecture Design and Optimization

Shurun Wang, Zhao Wang, Shiqi Wang +1

The visual signal compression is a long-standing problem. Fueled by the recent advances of deep learning, exciting progress has been made. Despite better compression performance, e…

cs.LG2021

Neuron Coverage-Guided Domain Generalization

Chris Xing Tian, Haoliang Li, Xiaofei Xie +2

This paper focuses on the domain generalization task where domain knowledge is unavailable, and even worse, only samples from a single domain can be utilized during training. Our m…

cs.CV2021

Camera Invariant Feature Learning for Generalized Face Anti-spoofing

Baoliang Chen, Wenhan Yang, Haoliang Li +2

There has been an increasing consensus in learning based face anti-spoofing that the divergence in terms of camera models is causing a large domain gap in real application scenario…

cs.MM2020★ 17 cited

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…

eess.IV2020

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…

cs.CV2020★ 158 cited

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…

eess.IV2020★ 1 cited

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…

cs.CV2020★ 1 cited

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…

cs.CV2020★ 82 cited

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…

cs.CV2020★ 98 cited

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…

cs.CR2020★ 13 cited

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…

cs.MM2020★ 1 cited

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…

eess.IV2020

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…

cs.CV2020★ 46 cited

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…

cs.MM2020★ 1 cited

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…

eess.IV2020★ 34 cited

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…