Publications

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● Preprints

Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approach
Mian Zou, Baosheng Yu, Yibing Zhan, Siwei Lyu, and Kede Ma
[arXiv]
Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method
Mian Zou, Baosheng Yu, Yibing Zhan, Siwei Lyu, and Kede Ma
[arXiv]
Comparison of No-Reference Image Quality Models via MAP Estimation in Diffusion Latents
Weixia Zhang, Dingquan Li, Guangtao Zhai, Xiaokang Yang, and Kede Ma
[arXiv]
Scanpath Prediction in Panoramic Videos via Expected Code Length Minimization
Mu Li, Kanglong Fan, and Kede Ma
[arXiv]
A Perceptually Optimized and Self-Calibrated Tone Mapping Operator
Peibei Cao, Chenyang Le, Yuming Fang, and Kede Ma
[arXiv]
Pseudocylindrical Convolutions for Learned Omnidirectional Image Compression
Mu Li, Kede Ma, Jinxing Li, and David Zhang
[arXiv] [GitHub]
Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Models
Wei Sun, Wen Wen, Xiongkuo Min, Long Lan, Guangtao Zhai, and Kede Ma
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
[arXiv] [GitHub]

● 2024

Learning Where to Edit Vision Transformers
Yunqiao Yang, Long-Kai Huang, Shengzhuang Chen, Kede Ma, and Ying Wei
Conference on Neural Information Processing Systems (NeurIPS), 2024.
[arXiv] [GitHub]
Perceptual Quality Assessment of Virtual Reality Videos in the Wild
Wen Wen, Mu Li, Yiru Yao, Xiangjie Sui, Yabin Zhang, Long Lan, Yuming Fang, and Kede Ma
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 34, no. 9, pp. 8368-8381, 2024.
[arXiv] [GitHub]
Learned HDR Image Compression for Perceptually Optimal Storage and Display
Peibei Cao, Haoyu Chen, Jingzhe Ma, Yu-Chieh Yuan, Zhiyong Xie, Xin Xie, Haiqing Bai, and Kede Ma
European Conference on Computer Vision (ECCV), 2024.
[arXiv] [GitHub]
Arbitrary-Scale Video Super-Resolution with Structural and Textural Priors
Wei Shang, Dongwei Ren, Wanying Zhang, Yuming Fang, Wangmeng Zuo, and Kede Ma
European Conference on Computer Vision (ECCV), 2024.
[arXiv] [GitHub]
Multiscale Sliced Wasserstein Distances as Perceptual Color Difference Measures
Jiaqi He, Zhihua Wang, Leon Wang, Tsein-I Liu, Yuming Fang, Qilin Sun, and Kede Ma
European Conference on Computer Vision (ECCV), 2024.
[arXiv] [GitHub]
A Comprehensive Study of Multimodal Large Language Models for Image Quality Assessment
Tianhe Wu, Kede Ma, Jie Liang, Yujiu Yang, and Lei Zhang
European Conference on Computer Vision (ECCV), 2024.
[arXiv] [GitHub]
Steerable Pyramid Transform Enables Robust Left Ventricle Quantification
Xiangyang Zhu, Kede Ma, and Wufeng Xue
Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2024.
[arXiv] [GitHub]
Hierarchical Prior-based Super Resolution for Point Cloud Geometry Compression
Dingquan Li, Kede Ma, Jing Wang, and Ge Li
IEEE Transactions on Image Processing (TIP), vol. 33, pp. 1965-1976, 2024.
[arXiv] [GitHub]
Task-Specific Normalization for Continual Learning of Blind Image Quality Models
Weixia Zhang, Kede Ma, Guangtao Zhai, and Xiaokang Yang
IEEE Transactions on Image Processing (TIP), vol. 33, pp. 1898-1910, 2024.
[arXiv] [GitHub]
Perceptual Assessment and Optimization of HDR Image Rendering
Peibei Cao, Rafał K. Mantiuk, and Kede Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
[arXiv] [GitHub]
Modular Blind Video Quality Assessment
Wen Wen, Mu Li, Yabin Zhang, Yiting Liao, Junlin Li, Li Zhang, and Kede Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
[arXiv] [GitHub]
Learned Scanpaths Aid Blind Panoramic Video Quality Assessment
Kanglong Fan, Wen Wen, Mu Li, Yifan Peng, and Kede Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
[arXiv]
Image Quality Assessment: Integrating Model-Centric and Data-Centric Approaches
Peibei Cao, Dingquan Li, and Kede Ma
Conference on Parsimony and Learning (CPAL), 2024.
[arXiv]

● 2023

IconShop: Text-Guided Vector Icon Synthesis with Autoregressive Transformers
Ronghuan Wu, Wanchao Su, Kede Ma, and Jing Liao
ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia), vol. 42(6), no. 230, pp.1-14, 2023.
[arXiv] [GitHub]
Measuring Perceptual Color Differences of Smartphone Photographs
Zhihua Wang, Keshuo Xu, Yang Yang, Jianlei Dong, Shuhang Gu, Lihao Xu, Yuming Fang, and Kede Ma
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 8, pp. 10114-10128, 2023.
[arXiv] [GitHub]
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective
Weixia Zhang, Guangtao Zhai, Ying Wei, Xiaokang Yang, and Kede Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[arXiv] [GitHub]
Learning a Deep Color Difference Metric for Photographic Images
Haoyu Chen, Zhihua Wang, Yang Yang, Qilin Sun, and Kede Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[arXiv] [GitHub]
Joint Video Multi-Frame Interpolation and Deblurring under Unknown Exposure Time
Wei Shang, Dongwei Ren, Yi Yang, Hongzhi Zhang, Kede Ma, and Wangmeng Zuo
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[arXiv] [GitHub]
Continual Learning for Blind Image Quality Assessment
Weixia Zhang, Dingquan Li, Chao Ma, Guangtao Zhai, Xiaokang Yang, and Kede Ma
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 3, pp. 2864-2878, 2023.
[arXiv] [GitHub]
Troubleshooting Image Segmentation Models with Human-in-the-Loop
Haotao Wang, Tianlong Chen, Zhangyang Wang, and Kede Ma
Springer Machine Learning (ML), vol. 112, pp. 1033-1051, 2023.
[pdf] [GitHub]
Subjective Quality Assessment of User-Generated 360° Videos
Yuming Fang, Yiru Yao, Xiangjie Sui, and Kede Ma
IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2023.
[pdf] [GitHub]

● 2022

Hiding Images in Deep Probabilistic Models
Haoyu Chen, Linqi Song, Zhenxing Qian, Xinpeng Zhang, and Kede Ma
Conference on Neural Information Processing Systems (NeurIPS), 2022.
[arXiv] [GitHub]
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop
Weixia Zhang, Dingquan Li, Xiongkuo Min, Guangtao Zhai, Guodong Guo, Xiaokang Yang, and Kede Ma
Conference on Neural Information Processing Systems (NeurIPS), 2022. (Spotlight)
[arXiv] [GitHub]
Active Fine-Tuning from gMAD Examples Improves Blind Image Quality Assessment
Zhihua Wang and Kede Ma
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 44, no. 9, pp. 4577-4590, 2022.
[arXiv]
Perceptual Quality Assessment of Omnidirectional Images as Moving Camera Videos
Xiangjie Sui, Kede Ma, Yiru Yao, and Yuming Fang
IEEE Transactions on Visualization and Computer Graphics (TVCG), vol. 28, no. 8, pp. 3022-3034, 2022.
[arXiv] [GitHub]
A Database of Visual Color Differences of Modern Smartphone Photography
Keshuo Xu*, Zhihua Wang*, Yang Yang, Jianlei Dong, Lihao Xu, Yuming Fang, and Kede Ma (*Equal contribution)
IEEE International Conference on Image Processing (ICIP), 2022.
[pdf]
Image Quality Assessment: Unifying Structure and Texture Similarity
Keyan Ding, Kede Ma, Shiqi Wang, and Eero P. Simoncelli
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 44, no. 5, pp. 2567-2581, 2022.
[arXiv] [GitHub]

● 2021

Perceptually Optimized Deep High-Dynamic-Range Image Tone Mapping
Chenyang Le, Jiebin Yan, Yuming Fang, and Kede Ma
IEEE International Conference on Virtual Reality and Visualization (ICVRV), 2021. (Best Paper Award)
[arXiv]
Image Quality Assessment in the Modern Age
Kede Ma and Yuming Fang
ACM Multimedia Tutorial (MM), 2021.
[arXiv] [project page]
Locally Adaptive Structure and Texture Similarity for Image Quality Assessment
Keyan Ding, Yi Liu, Xueyi Zou, Shiqi Wang, and Kede Ma
ACM Multimedia (MM), 2021.
[arXiv] [GitHub]
Semi-Supervised Deep Ensembles for Blind Image Quality Assessment
Zhihua Wang, Dingquan Li, and Kede Ma
International Joint Conference on Artificial Intelligence
Workshop on Weakly Supervised Representation Learning (IJCAIW), 2021. (Best Paper Runner-Up)
[arXiv] [GitHub]
Debiased Subjective Assessment of Real-World Image Enhancement
Peibei Cao, Zhangyang Wang, and Kede Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[arXiv]
Troubleshooting Blind Image Quality Models in the Wild
Zhihua Wang, Haotao Wang, Tianlong Chen, Zhangyang Wang, and Kede Ma
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[arXiv]
Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild
Weixia Zhang, Kede Ma, Guangtao Zhai, and Xiaokang Yang
IEEE Transactions on Image Processing (TIP), vol. 30, pp. 3474-3486, 2021.
[arXiv] [GitHub]
Exposing Semantic Segmentation Failures via Maximum Discrepancy Competition
Jiebin Yan, Yu Zhong, Yuming Fang, Zhangyang Wang, and Kede Ma
International Journal of Computer Vision (IJCV), vol. 129, no. 5, pp. 1768-1786, 2021.
[arXiv] [GitHub]
Comparison of Full-Reference Image Quality Models for Optimization of Image Processing Systems
Keyan Ding, Kede Ma, Shiqi Wang, and Eero P. Simoncelli
International Journal of Computer Vision (IJCV), vol. 129, no. 4, pp. 1258-1281, 2021.
[arXiv] [GitHub]

● 2020

Learning to Blindly Assess Image Quality in the Laboratory and Wild
Weixia Zhang, Kede Ma, Guangtao Zhai, and Xiaokang Yang
IEEE International Conference on Image Processing (ICIP), 2020.
[arXiv] [GitHub]
Characterizing Generalized Rate-Distortion Performance of Video Coding: An Eigen Analysis Approach
Zhengfang Duanmu*, Wentao Liu*, Zhuoran Li, Kede Ma, and Zhou Wang (*Equal contribution)
IEEE Transactions on Image Processing (TIP), vol. 29, pp. 6180-6193, 2020.
[arXiv] [GitHub]
Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression
Mu Li, Kede Ma, Jane You, David Zhang, and Wangmeng Zuo
IEEE Transactions on Image Processing (TIP), vol. 29, pp. 5900-5911, 2020.
[arXiv] [GitHub]
Fast Multi-Scale Structural Patch Decomposition for Multi-Exposure Image Fusion
Hui Li, Kede Ma, Hongwei Yong, and Lei Zhang
IEEE Transactions on Image Processing (TIP), vol. 29, pp. 5805-5816, 2020.
[pdf] [GitHub]
Perceptual Quality Assessment of Smartphone Photography
Yuming Fang, Hanwei Zhu, Yan Zeng, Kede Ma, and Zhou Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
[pdf] [GitHub]
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively
Haotao Wang, Tianlong Chen, Zhangyang Wang, and Kede Ma
International Conference on Learning Representations (ICLR), 2020.
[arXiv] [open review] [GitHub]
Deep Guided Learning for Fast Multi-Exposure Image Fusion
Kede Ma, Zhengfang Duanmu, Hanwei Zhu, Yuming Fang, and Zhou Wang
IEEE Transactions on Image Processing (TIP), vol. 29, pp. 2808-2819, 2020.
[pdf] [GitHub]
Perceptual Evaluation for Multi-Exposure Image Fusion of Dynamic Scenes
Yuming Fang, Hanwei Zhu, Kede Ma, Zhou Wang, and Shutao Li
IEEE Transactions on Image Processing (TIP), vol. 29, pp. 1127-1138, 2020.
[pdf] [GitHub]
Group Maximum Differentiation Competition: Model Comparison with Few Samples
Kede Ma, Zhengfang Duanmu, Zhou Wang, Qingbo Wu, Wentao Liu, Hongwei Yong, Hongliang Li, and Lei Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 42, no. 4, pp. 851-864, Apr. 2020.
[pdf] [project page]
Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
Weixia Zhang, Kede Ma, Jia Yan, Dexiang Deng, and Zhou Wang
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 30, no. 1, pp. 36-47, Jan. 2020.
[arXiv] [GitHub]

● 2019

Blind Image Quality Assessment by Learning from Multiple Annotators
Kede Ma, Xuelin Liu, Yuming Fang, and Eero P. Simoncelli
IEEE International Conference on Image Processing (ICIP), 2019.
[pdf]
Intrinsic Image Popularity Assessment
Keyan Ding, Kede Ma, and Shiqi Wang
ACM Multimedia (MM), 2019.
[arXiv] [GitHub]

● 2018

Quality-of-Experience for Adaptive Streaming Videos: An Expectation Confirmation Theory Motivated Approach
Zhengfang Duanmu, Kede Ma, and Zhou Wang
IEEE Transactions on Image Processing (TIP), vol. 27, no. 12, pp. 6135-6146, Dec. 2018.
[pdf]
Deep Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks
Kede Ma, Huan Fu, Tongliang Liu, Zhou Wang, and Dacheng Tao
IEEE Transactions on Image Processing (TIP), vol. 27, no. 10, pp. 5155-5166, Oct. 2018.
[arXiv] [Caffe code]
Blind Image Quality Assessment Using Local Consistency Aware Retriever and Uncertainty Aware Evaluator
Qingbo Wu, Hongliang Li, King N. Ngan, and Kede Ma
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 28, no. 9, pp. 2078-2089, Sep. 2018.
[pdf]
Multi-Exposure Image Fusion by Optimizing A Structural Similarity Index
Kede Ma, Zhengfang Duanmu, Hojatollah Yeganeh, and Zhou Wang
IEEE Transactions on Computational Imaging (TCI), vol. 4, no. 1, pp. 60-72, Mar. 2018.
[pdf] [Matlab code] [data set]
End-to-End Blind Image Quality Assessment Using Deep Neural Networks
Kede Ma, Wentao Liu, Kai Zhang, Zhengfang Duanmu, Zhou Wang, and Wangmeng Zuo
IEEE Transactions on Image Processing (TIP), vol. 27, no. 3, pp. 1202-1213, Mar. 2018.
[pdf] [project page]
Geometric Transformation Invariant Image Quality Assessment Using Convolutional Neural Networks
Kede Ma, Zhengfang Duanmu, and Zhou Wang
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018.
[pdf] [Tensorflow code]
A Hybrid Quality Metric for Non-Integer Image Interpolation
Jinling Chen, Yiwen Xu, Kede Ma, Huiwen Huang, and Tiesong Zhao
Tenth International Conference on Quality of Multimedia Experience (QoMEX), 2018.
[pdf]

● 2017

Blind Image Quality Assessment: Exploiting New Evaluation and Design Methodologies
Kede Ma
University of Waterloo, 2017. (Finalist for the Governor General’s Gold Medal)
[link]
Advisor: Prof. Zhou Wang
Unified Blind Quality Assessment of Compressed Natural, Graphic, and Screen Content Images
Xiongkuo Min, Kede Ma, Ke Gu, Guangtao Zhai, Zhou Wang, and Weisi Lin
IEEE Transactions on Image Processing (TIP), vol. 26, no. 11, pp. 5462-5474, Nov. 2017.
[pdf] [project page]
dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs
Kede Ma, Wentao Liu, Tongliang Liu, Zhou Wang, and Dacheng Tao
IEEE Transactions on Image Processing (TIP), vol. 26, no. 8, pp. 3951-3964, Aug. 2017.
[arXiv] [Matlab code]
Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach
Kede Ma, Hui Li, Hongwei Yong, Zhou Wang, Deyu Meng, and Lei Zhang
IEEE Transactions on Image Processing (TIP), vol. 26, no. 5, pp. 2519-2532, May 2017.
[pdf] [sup] [Matlab code]
Perceptual Depth Quality in Distorted Stereoscopic Images
Jiheng Wang, Shiqi Wang, Kede Ma, and Zhou Wang
IEEE Transactions on Image Processing (TIP), vol. 26, no. 3, pp. 1202-1215, Mar. 2017.
[pdf] [project page]
Waterloo Exploration Database: New Challenges for Image Quality Assessment Models
Kede Ma, Zhengfang Duanmu, Qingbo Wu, Zhou Wang, Hongwei Yong, Hongliang Li, and Lei Zhang
IEEE Transactions on Image Processing (TIP), vol. 26, no. 2, pp. 1004-1016, Feb. 2017.
[pdf] [project page]
A Quality-of-Experience Index for Streaming Video
Zhengfang Duanmu, Kai Zeng, Kede Ma, Abdul Rehman, and Zhou Wang
IEEE Journal of Selected Topics in Signal Processing (JSTSP), vol. 11, no. 1, pp. 154-166, Feb. 2017.
[pdf] [project page]
Quality-of-Experience of Adaptive Video Streaming: Exploring the Space of Adaptations
Zhengfang Duanmu, Kede Ma, and Zhou Wang
ACM Multimedia (MM), 2017.
[pdf] [project page]
Perceptual Quality Assessment of HDR Deghosting Algorithms
Yuming Fang, Hanwei Zhu, Kede Ma, and Zhou Wang
IEEE International Conference on Image Processing (ICIP), 2017.
[pdf]

● 2016

Group MAD Competition − A New Methodology to Compare Objective Image Quality Models
Kede Ma, Qingbo Wu, Zhou Wang, Zhengfang Duanmu, Hongwei Yong, Hongliang Li, and Lei Zhang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (Spotlight)
[pdf] [project page]

● 2015

A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images
Shiqi Wang, Kede Ma, Hojatollah Yeganeh, Zhou Wang, and Weisi Lin
IEEE Signal Processing Letters (SPL), vol. 22, no. 12, pp. 2387-2390, Dec. 2015.
[pdf] [Matlab code]
Objective Quality Assessment for Color-to-Gray Image Conversion
Kede Ma, Tiesong Zhao, Kai Zeng, and Zhou Wang
IEEE Transactions on Image Processing (TIP), vol. 24, no. 12, pp. 4673-4685, Dec. 2015.
[pdf] [Matlab code]
Perceptual Quality Assessment for Multi-Exposure Image Fusion
Kede Ma, Kai Zeng, and Zhou Wang
IEEE Transactions on Image Processing (TIP), vol. 24, no. 11, pp. 3345-3356, Nov. 2015.
[pdf] [Matlab code] [data set]
High Dynamic Range Image Compression by Optimizing Tone Mapped Image Quality Index
Kede Ma, Hojatollah Yeganeh, Kai Zeng, and Zhou Wang
IEEE Transactions on Image Processing (TIP), vol. 24, no. 10, pp. 3086-3097, Oct. 2015.
[pdf] [Matlab code] [data set](upon request)
No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics
Yuming Fang, Kede Ma, Zhou Wang, Weisi Lin, Zhijun Fang, and Guangtao Zhai
IEEE Signal Processing Letters (SPL), vol. 22, no. 7, pp. 838-842, Jul. 2015.
[pdf] [Matlab code]
Multi-Exposure Image Fusion: A Patch-wise Approach
Kede Ma and Zhou Wang
IEEE International Conference on Image Processing (ICIP), 2015. (Top 10% Award)
[pdf] [Matlab code]
Perceptual Evaluation of Single Image Dehazing Algorithms
Kede Ma, Wentao Liu, and Zhou Wang
IEEE International Conference on Image Processing (ICIP), 2015.
[pdf] [data set]

● 2014

Recursive Code Construction for Reversible Data Hiding in DCT Domain
Biao Chen Weiming Zhang, Kede Ma, and Nenghai Yu
Multimedia Tools and Applications, vol. 72, no. 2, pp. 1985-2009, Sep. 2014.
[pdf]
Reversibility Improved Data Hiding in Encrypted Images
Weiming Zhang, Kede Ma, and Nenghai Yu
Signal Processing, vol. 94, pp. 118-127, Jan. 2014.
[pdf]
Perceptual Evaluation of Multi-Exposure Image Fusion Algorithms
Kai Zeng, Kede Ma, Rania Hassen, and Zhou Wang
Sixth International Workshop on Quality of Multimedia Experience (QoMEX), 2014.
[pdf]
High Dynamic Range Image Tone Mapping by Optimizing Tone Mapped Image Quality Index
Kede Ma, Hojatollah Yeganeh, Kai Zeng, and Zhou Wang
IEEE International Conference on Multimedia and Expo (ICME), 2014. (Oral)
[pdf]

● 2013

Reversible Data Hiding in Encrypted Images by Reserving Room before Encryption
Kede Ma, Weiming Zhang, Xianfeng Zhao, Nenghai Yu, and Fenghua Li
IEEE Transactions on Information Forensics and Security (TIFS), vol. 8, no. 3, pp. 553-562, Mar. 2013.
[pdf] [Matlab code]
Last updated: July 15, 2024.