刘贤明科研成果

Profile Research Group 新建主栏目 Basic Information 名称 Dr. Xianming Liu is a Professor, Ph.D advisor with the Department of Computer Science, Harbin Institute of Technology (HIT), Harbin, China. He received the B.S., M.S., and Ph.D degrees in computer science from HIT under the supervision of Prof. Debin Zhao and Prof. Wen Gao, in 2006, 2008 and 2012, respectively. In 2007, he joined the Joint Research and Development Lab (JDL), Chinese Academy of Sciences, Beijing, as a research assistant. From 2009 to 2012, he was with National Engineering Lab for Video Technology, Peking University, Beijing, as a research assistant. In 2011, he spent half a year at the Department of Electrical and Computer Engineering, McMaster University, Canada, as a visiting student. From December 2012 to December 2013, he worked as a post-doctoral fellow at McMaster University, Hamilton, Canada, working with Prof. Xiaolin Wu. From January 2014 to March 2017, he worked with Prof. Gene Cheung as a project researcher at National Institute of Informatics (NII), Tokyo, Japan. He is the receipt of IEEE ICME 2016 Best Student Paper Award and IFTC2016 Best Paper Award. His research interests include trustworthy AI, 3D signal processing and biomedical signal processing. 刘贤明，现任哈尔滨工业大学计算机学院长聘教授、博士生导师、副院长，国家自然科学优秀青年基金获得者，哈工大青年科学家工作室学术带头人。2012年从哈工大计算机学院获得博士学位，博士毕业后，先后在加拿大麦克马斯特大学、日本国立情报学研究所担任博士后研究员和特任研究员。2013年4月留校任讲师，2014年秋和2016年秋两次入选哈工大青年拔尖人才，分别破格提升副教授、教授。研究方向为可信机器学习、多媒体信息处理，在TPAMI/TIP/ICLR/ICML/CVPR/ICCV/ECCV/AAAI/IJCAI等国际顶级期刊和会议上发表论文200余篇。获得黑龙江省青年科技奖、中国人工智能学会第八届吴文俊人工智能优秀青年奖、IEEE多媒体领域旗舰会议ICME2016最佳学生论文奖和Springer IFTC2016最佳论文奖。担任ACM Multimedia, IEEE ICME/ICIP/ICASSP等多个国际会议程序委员会委员、Special Section Chair、Area Chair。主持国家重点研发计划重点专项项目、国家自然科学基金优青、重大研究计划、面上和青年项目、中国博士后特别资助、黑龙江省博士后青年英才计划、哈工大青年拔尖人才支持计划等项目。 招收2024级硕士生（含推免、考研） 招收2024级博士生 1）招收博士生1-2名，研究方向为可信赖机器学习。要求：数学好，编程好，英语好，尤其欢迎有ACM竞赛经历和数学专业的同学。 2）招收博士生1-2名，研究方向为计算摄像、三维视觉信息处理。要求：数学好，编程好，英语好，尤其欢迎有ACM竞赛经历和光学专业的同学。 3）与香港城市大学王诗淇教授联合招收联合培养博士生，同时获得哈工大和香港城市大学博士学位，研究方向：生物医学信息处理、计算机视觉。 4）招收硕士生3-6名。要求：数学好，编程好，英语好，尤其欢迎有ACM竞赛经历的同学。 5）常年招聘博士后（优秀者可转助理教授） 邮箱地址： Research Interests 名称 Broadly interested in multimedia signal processing, biomedical signal processing and machine learning: Trustworthy AI, including robust learning with imperfect labels, few/zero-shot learning, federated learning, adversarial attack and defense, etc; Computational imaging, including low-level image reconstruction and enhancement, microscopy imaging, etc; Biomedical signal compression, including lossless/near-lossless compression for medical images and genomics data; 3D signal processing and analysis, including mesh denoising, point clouds usampling, point clouds analysis. Publications 名称 * denotes corresponding author 表示通讯作者 # denotes equal contribution 表示共同一作 2024 [1] Yuanchao Bai, Xianming Liu*, Kai Wang, Xiangyang Ji, Xiaolin Wu, Wen Gao, "Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression", accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (CCF-A). [2] Xiong Zhou, Xianming Liu*, Hanzhang Wang, Deming Zhai, Junjun Jiang, Xiangyang Ji, "On the Dynamics under the Unhinged Loss and Beyond", accepted by Journal of Machine Learning Research (CCF-A). [3] Chenyang Wang, Junjun Jiang, Kui Jiang, Xianming Liu, "Low-Light Face Super-Resolution via Illumination, Structure, and Texture Associated Representation", accepted by AAAI 2024 (CCF-A). [4] Gang Wu, Junjun Jiang, Kui Jiang, Xianming Liu, "Learning from History: A Self-Prior Guided, Self-Promoted Approach for Image Restoration", accepted by AAAI 2024 (CCF-A). [5] Kui Jiang, Junjun Jiang, Xianming Liu, Xin Xu, Xianzheng Ma, "FMRNet: Image Deraining via Frequency Mutual Revision", accepted by AAAI 2024 (CCF-A). [6] Xiong Zhou, Xianming Liu*, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji, "Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data", In Proceedings of the International Conference on Learning Representations (ICLR2024)【清华A类会议，机器学习三大顶会之一】 [7] Xiong Zhou, Xianming Liu*, Feilong Zhang, Gang Wu, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Zero-Mean Regularized Spectral Contrastive Learning", In Proceedings of the International Conference on Learning Representations (ICLR2024)【清华A类会议，机器学习三大顶会之一】 [8] Pengwei Liang, Junjun Jiang, Xianming Liu, Jiayi Ma, "Image Deblurring by Exploring In-depth Properties of Transformer", accepted by IEEE Transactions on Neural Networks and Learning Systems. [9] Fahu Ji, Qian Zhou, Jue Ruan, Zexuan Zhu, Xianming Liu*, "A Compressive Seeding Algorithm in Conjunction with Reordering-based Compression", accepted by Bioinformatics [10] Yuchen Pan, Junjun Jiang, Kui Jiang, Zhihao Wu, Keyuan Yu, Xianming Liu, "OpticalDR: A Deep Optical Imaging Model for Privacy-Protective Depression Recognition", accepted by CVPR 2024 (CCF-A). [11] Gang Wu, Junjun Jiang, Kui Jiang, Xianming Liu, "Exploring the Self-Supervised Constraints in Image Super-Resolution", accepted by ICME2024 [12] Chenyang Wang, Junjun Jiang, Xianming Liu, "Exploring the Self-Supervised Constraints in Image Super-Resolution", accepted by IEEE Transactions on Biometrics, Behavior, and Identity Science [13] Qian Zhou, Fahu Ji, Dongxiao Lin, Xianming Liu, Zexuan Zhu, Jue Ruan,"KSNP: a fast de Bruijn graph-based haplotyping tool approaching data-in time cost", accepted by Nature Communications [14] Ziqi Bai, Xianming Liu*, Cheng Guo, Kui Jiang, Junjun Jiang, Xiangyang Ji, "HoloFormer: Contrastive Regularization based Transformer for Holographic Image Reconstruction", accepted by IEEE Transactions on Computational Imaging 2023 [1] Xiong Zhou, Xianming Liu*, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Asymmetric Loss Functions for Noise-tolerant Learning: Theory and Applications", accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (CCF-A). [2] Wenbo Zhao, Xianming Liu*, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Self-Supervised Arbitrary-Scale Implicit Point Clouds Upsampling", accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (CCF-A). [3] Chenyang Wang, Junjun Jiang, Xiong Zhou, Xianming Liu, "ReSmooth: Detecting and Utilizing OOD Samples when Training with Data Augmentation", accepted by IEEE Transactions on Neural Networks and Learning Systems. [4] Zhiwei Zhong, Xianming Liu*, Junjun Jiang, Debin Zhao, Xiangyang Ji, "Guided Depth Map Super-resolution: A Survey", accepted by ACM Computing Surveys. [5] Chenyang Wang, Junjun Jiang, Zhiwei Zhong, Xianming Liu, "Spatial-Frequency Mutual Learning for Face Super-Resolution", accepted by CVPR2023 （CCF-A） [6] Zhiwei Zhong, Xianming Liu*, Junjun Jiang, Debin Zhao, Xiangyang Ji, "Deep Attentional Guided Image Filtering", accepted by IEEE Transactions on Neural Networks and Learning Systems. [7] Kai Wang, Yuanchao Bai, Deming Zhai, Daxin Li, Junjun Jiang, Xianming Liu*, "Learning Lossless Image Compression for High Bit-Depth Medical Imaging ", accepted by ICME2023 [8] Chenyang Wang, Junjun Jiang, Zhiwei Zhong, Deming Zhai, Xianming Liu, "Super-Resolving Face Image by Facial Parsing Information", accepted by IEEE Transactions on Biometrics, Behavior, and Identity Science. [9] Feilong Zhang, Yinchuan Li, Shiyi Lin, Yunfeng shao, Junjun Jiang, Xianming Liu*, "Large Sparse Kernels for Federated Learning", accepted by ICLR2023 (Tiny Paper) [10] Shiyi Lin, Deming Zhai, Feilong Zhang, Junjun Jiang, Xianming Liu*, Xiangyang Ji, "Overhead-Free Noise-Tolerant Federated Learning: A New Baseline", accepted by Machine Intelligence Research [11] Feilong Zhang, Xianming Liu*, Shiyi Lin, Gang Wu, Xiong Zhou, Junjun Jiang, Xiangyang Ji, "No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation", accepted by ICML2023 (CCF-A) [12] Hanzhang Wang, Deming Zhai, Xianming Liu, Junjun Jiang, Wen Gao, "Unsupervised Deep Exemplar Colorization via Pyramid Dual Non-local Attention", IEEE Transactions on Image Processing, 2023 （CCF-A） [13] Gang Wu, Junjun Jiang, Xianming Liu, "A Practical Contrastive Learning Framework for Single Image Super-Resolution", accepted by IEEE Transactions on Neural Networks and Learning Systems. [14] Li, Z., Chen, Z., Liu, X. Jiang, J. DepthFormer: Exploiting Long-range Correlation and Local Information for Accurate Monocular Depth Estimation. Machine Intelligence Research (2023). 2022 [1] Wenbo Zhao, Xianming Liu*, Junjun Jiang, Debin Zhao, Ge Li, Xiangyang Ji, "Local Surface Descriptor for Geometry and Feature Preserved Mesh Denoising", AAAI2022（CCF-A） [2] Yuanchao Bai#, Xu Yang#, Xianming Liu*, Junjun Jiang, Yaowei Wang, Xiangyang Ji, Wen Gao, "Towards End-to-End Image Compression and Analysis with Transformers", AAAI2022（CCF-A） [3] Zhenyu Li, Zehui Chen, Ang Li, Liangji Fang, Qinhong Jiang, Xianming Liu, Junjun Jiang, Bolei Zhou, Hang Zhao, "SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations", AAAI2022（CCF-A） [4] Xiong Zhou, Xianming Liu*, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji, "Learning Towards the Largest Margins", ICLR2022 【机器学习三大顶会之一】 [5] Yiqi Zhong, Xianming Liu*, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon", CVPR2022（CCF-A）【code】 [6] Wenbo Zhao, Xianming Liu*, Zhiwei Zhong, Junjun Jiang, Wei Gao, Ge Li, Xiangyang Ji, "Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation", CVPR2022（CCF-A） [7] Qing Ma, Junjun Jiang, Xianming Liu, Jiayi Ma, "Multi-task Interaction learning for Spatiospectral Image Super-Resolution", To appear in IEEE Transactions on Image Processing, 2022 （CCF-A） [8] 江俊君，李震宇，刘贤明，"基于深度学习的单目深度估计方法综述"，计算机学报 （CCF-A） [9] Pengwei Liang, Junjun Jiang, Xianming Liu, Jiayi Ma, "BaMBNet: A Blur-aware Multi-branch Network for Dual-Pixel Defocus Deblurring", To appear in IEEE/CAA Journal of Automatica Sinica (自动化学报英文版，CCF-T1) [10] Zhenyu Li, Junjun Jiang, Xianming Liu, "Self-supervised Monocular Depth Estimation via Discrete Strategy and Uncertainty", To appear in IEEE/CAA Journal of Automatica Sinica (自动化学报英文版，CCF-T1) [11] Xiong Zhou, Xianming Liu*, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji, "Prototype-anchored Learning for Learning with Imperfect Annotations", ICML2022 (CCF-A). [12] Chenyang Wang, Junjun Jiang, Zhiwei Zhong, Xianming Liu, "Propagating Facial Prior Knowledge for Multi-Task Learning in Face Super-Resolution", To appearin IEEE Transactions on Circuits and Systems for Video Technology, 2022 [13] Cheng Guo, Xianming Liu, Feilong Zhang, Yongbin Du, Shenghao Zheng, Zehua Wang, Xiaoqing Zhang, Xingchi Kan, Zhengjun Liu, and Weibo Wang, "Lensfree on-chip microscopy based on single-plane phase retrieval", Optics Express, Vol. 30, Issue 11, pp. 19855-19870 (2022) [14] Tong Shao, Deming Zhai, Junjun Jiang, Xianming Liu, "Hybrid Conditional Deep Inverse Tone Mapping", ACM Multimedia 2022 (CCF-A) [15] Jinwang Pan, Deming Zhai, Yuanchao Bai, Junjun Jiang, Debin Zhao, Xianming Liu, "ChebyLighter: Optimal Curve Estimation for Low-light Image Enhancement", ACM Multimedia 2022 (CCF-A) [16] Jialei Xu, Xianming Liu*, Yuanchao Bai, Junjun Jiang, Kaixuan Wang, Xiaozhi Chen, Xiangyang Ji, "Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation", ACM Multimedia 2022 (CCF-A) [17] Zhenyu Li, Zehui Chen, Ang Li, Liangji Fang, Qinhong Jiang, Xianming Liu, Junjun Jiang, "Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Training", ECCV2022【计算机视觉三大顶会之一】 [18] Pengwei Liang, Junjun Jiang, Xianming Liu, Jiayi Ma, "Fusion from Decomposition: A Self-Supervised Decomposition Approach for Image Fusion", ECCV2022【计算机视觉三大顶会之一】 [19] Yi Niu, Mingming Ma, Fu Li, Xianming Liu, Guangming Shi: ACO: lossless quality score compression based on adaptive coding order. BMC Bioinformatics. 23(1): 219 (2022) 2021 [1] Zhiwei Zhong, Xianming Liu*, Junjun Jiang, Debin Zhao, Zhiwen Chen, Xiangyang Ji, "High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion", To appear in IEEE Transactions on Image Processing, 2021 （CCF-A）. [2] Wei Hu, Jiahao Pang, Xianming Liu, Dong Tian, Chia-Wen Lin, Anthony Vetro, "Graph Signal Processing for Geometric Data and Beyond: Theory and Applications", To appear in IEEE Transactions on Multimedia, 2021. [3] Bo Pang, Deming Zhai, Junjun Jiang, Xianming Liu, "Fully Unsupervised Person Re-identification via Selective Contrastive Learning", To appear in ACM Transactions on Multimedia Computing Communications and Applications (ACM TOMM), 2021. [4] Junjun Jiang, Chenyang Wang, Xianming Liu, Jiayi Ma, "Deep Learning-based Face Super-resolution: A Survey", To appear in ACM Computing Surveys, 2021. [5] Xiong Zhou, Xianming Liu*, Chenyang Wang, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Learning with Noisy Labels via Sparse Regularization", ICCV2021 (CCF-A). [6] Wenbo Zhao, Xianming Liu, Xiaopeng Fan, Debin Zhao, "NormalNet: Learning-based Mesh Normal Denoising via Local Partition Normalization", To appear in IEEE Transactions on Circuits and Systems for Video Technology. [7] Jiliang Yan, Deming Zhai, Junjun Jiang, Xianming Liu, "Target-guided Adaptive Base Class Reweighting for Few-Shot Learning", ACM Multimedia 2021 (CCF-A). [8] Xiong Zhou, Xianming Liu*, Junjun Jiang, Xin Gao, Xiangyang Ji, "Asymmetric Loss Functions for Learning with Noisy Labels", ICML2021 (CCF-A). [9] Feilong Zhang, Xianming Liu*, Cheng Guo, Shiyi Lin, Junjun Jiang, Xiangyang Ji, “Physics-based Iterative Projection Complex Neural Network for Phase Retrieval in Lensless Microscopy Imaging”，CVPR2021 (CCF-A). [10] Yuanchao Bai, Xianming Liu*, Wangmeng Zuo, Yaowei Wang, Xiangyang Ji, "Learning Scalable L∞-constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression"， CVPR2021 (CCF-A). [11] 李强，刘贤明*，韩凯歌，江俊君，季向阳，“基于深度学习的数字病理扫描系统单次曝光自动对焦方法”，中国科学: 信息科学（CCF-A类中文期刊） [12] Qiang Li, Xianming Liu*, Kaige Han, Cheng Guo, Junjun Jiang, Xiangyang Ji, Xiaolin Wu, “Learning to Autofocus in Whole Slide Imaging via Physics-guided Deep Cascade Networks," Optics Express, DOI:10.1364/OE.416824, January 2021 [13] Qiang Li, Xianming Liu*, Junjun Jiang, Cheng Guo, Xiangyang Ji, Xiaolin Wu, “Rapid Whole Slide Imaging via Dual-shot Deep Autofocusing," IEEE Transactions on Computational Imaging, vol. 7, pp. 124-136, 2021 2020 [1] Bo Pang, Deming Zhai, Junjun Jiang, Xianming Liu, “Single Image Deraining via Scale-space Invariant Attention Neural Network", in Proceedings of the 28th ACM International Conference on Multimedia (MM’20), October 12–16, 2020, Seattle, WA, USA，9 pages. (Oral) [2] Junjun Jiang, He Sun, Xianming Liu*, and Jiayi Ma, “Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery,” To appear in IEEE Transactions on Computational Imaging (TCI), 2020 [3] Junjun Jiang, Jiayi Ma, and Xianming Liu. "Multi-Layer Spectral-Spatial Graphs for Label Noisy Robust Hyperspectral Image Classification", To appear in IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020. [4] Wenbo Zhao, Xianming Liu*, Shiqi Wang, Xiaopeng Fan, Debin Zhao, "Graph-based Feature-Preserving Mesh Normal Filtering," IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020. [5] Xianming Liu, Deming Zhai, Yuanchao Bai, Xiangyang Ji, Wen Gao: Contrast Enhancement via Dual Graph Total Variation-Based Image Decomposition. IEEE Trans. Circuits Syst. Video Technol. 30(8): 2463-2476 (2020) [6] Yongbing Zhang, Yihui Feng, Xianming Liu*, Deming Zhai, Xiangyang Ji, Haoqian Wang, Qionghai Dai: Color-Guided Depth Image Recovery With Adaptive Data Fidelity and Transferred Graph Laplacian Regularization. IEEE Trans. Circuits Syst. Video Technol 30(2): 320-333 (2020) [7] Yuanchao Bai, Huizhu Jia, Ming Jiang, Xianming Liu, Xiaodong Xie, Wen Gao: Single-Image Blind Deblurring Using Multi-Scale Latent Structure Prior. IEEE Trans. Circuits Syst. Video Technol. 30(7): 2033-2045 (2020) [8] Yongsen Zhao, Deming Zhai, Junjun Jiang, Xianming Liu: ADRN: Attention-Based Deep Residual Network for Hyperspectral Image Denoising. ICASSP 2020: 2668-2672 [9] Chenyang Wang, Zhiwei Zhong, Junjun Jiang, Deming Zhai, Xianming Liu: Parsing Map Guided Multi-Scale Attention Network For Face Hallucination. ICASSP 2020: 2518-2522 [10] Zhanjian Shen, Deming Zhai, Xianming Liu, Junjun Jiang: SEMI-SUPERVISED GRAPH CONVOLUTIONAL HASHING NETWORK FOR LARGE-SCALE CROSS-MODAL RETRIEVAL, ICIP 2020. 2019 [1] Junjun Jiang, Jiayi Ma, Zheng Wang, Chen Chen, Xianming Liu: Hyperspectral Image Classification in the Presence of Noisy Labels. IEEE Trans. Geosci. Remote. Sens. 57(2): 851-865 (2019) [2] Deming Zhai, Xianming Liu*, Xiangyang Ji, Debin Zhao, Wen Gao: Joint Gaze Correction and Face Beautification for Conference Video Using Dual Sparsity Prior. IEEE Trans. Ind. Electron. 66(12): 9601-9611 (2019) [3] Junjun Jiang, Yi Yu, Zheng Wang, Xianming Liu, Jiayi Ma: Graph-Regularized Locality-Constrained Joint Dictionary and Residual Learning for Face Sketch Synthesis. IEEE Trans. Image Process. 28(2): 628-641 (2019) [4] Xianming Liu, Deming Zhai, Rong Chen, Xiangyang Ji, Debin Zhao, Wen Gao: Depth Restoration From RGB-D Data via Joint Adaptive Regularization and Thresholding on Manifolds. IEEE Trans. Image Process. 28(3): 1068-1079 (2019) [5] Xianming Liu, Gene Cheung, Xiangyang Ji, Debin Zhao, Wen Gao: Graph-Based Joint Dequantization and Contrast Enhancement of Poorly Lit JPEG Images. IEEE Trans. Image Process. 28(3): 1205-1219 (2019) [6] Yuanchao Bai, Gene Cheung, Xianming Liu, Wen Gao: Graph-Based Blind Image Deblurring From a Single Photograph. IEEE Trans. Image Process. 28(3): 1404-1418 (2019) [7] Xianming Liu, Deming Zhai, Rong Chen, Xiangyang Ji, Debin Zhao, Wen Gao: Depth Super-Resolution via Joint Color-Guided Internal and External Regularizations. IEEE Trans. Image Process. 28(4): 1636-1645 (2019) [8] Yuanchao Bai, Gene Cheung, Fen Wang, Xianming Liu, Wen Gao: Reconstruction-cognizant Graph Sampling Using Gershgorin Disc Alignment. ICASSP 2019: 5396-5400 [9] Cheng Guo, Xianming Liu, Xingchi Kan, Feilong Zhang, Jiubin Tan, Shutian Liu, and Zhengjun Liu, "Lensfree on-chip microscopy based on dual-plane phase retrieval," Optical Express 27(24), 35216-35229 (2019) [10] Cheng Guo, Xianming Liu, Xinchi Kan, Feilong Zhang, Jiubin Tan, Shutian Liu, Cuimei Tan, Zhengjun Liu, "Artifactless lensfree coherent microscopy with quasi-three-dimensional scanning," Measurement Science and Technology (31)4 , 2019 2018 [1] Xianming Liu, Gene Cheung, Chia-Wen Lin, Debin Zhao, Wen Gao: Prior-Based Quantization Bin Matching for Cloud Storage of JPEG Images. IEEE Trans. Image Process. 27(7): 3222-3235 (2018) [2] Deming Zhai, Xianming Liu, Hong Chang, Yi Zhen, Xilin Chen, Maozu Guo, Wen Gao: Parametric local multiview hamming distance metric learning. Pattern Recognit. 75: 250-262 (2018) [3] Yutao Liu, Guangtao Zhai, Ke Gu, Xianming Liu, Debin Zhao, Wen Gao: Reduced-Reference Image Quality Assessment in Free-Energy Principle and Sparse Representation. IEEE Trans. Multimedia 20(2): 379-391 (2018) [4] Deming Zhai, Xianming Liu, Xiangyang Ji, Debin Zhao, Shin'ichi Satoh, Wen Gao: Supervised Distributed Hashing for Large-Scale Multimedia Retrieval. IEEE Trans. Multimedia 20(3): 675-686 (2018) [5] Qiang Song, Ruiqin Xiong, Xiaopeng Fan, Xianming Liu, Tiejun Huang, Wen Gao: Compressed Image Restoration via External-Image Assisted Band Adaptive PCA Model Learning. DCC 2018: 97-106 [6] Yuanchao Bai, Gene Cheung, Xianming Liu, Wen Gao: Blind Image Deblurring Via Reweighted Graph Total Variation. ICASSP 2018: 1822-1826 [7] Zhaohui Che, Guangtao Zhai, Jing Liu, Ke Gu, Patrick Le Callet, Jiantao Zhou, Xianming Liu: A Blind Quality Measure for Industrial 2D Matrix Symbols Using Shallow Convolutional Neural Network. ICIP 2018: 2481-2485 [8] Rong Chen, Deming Zhai, Xianming Liu, Debin Zhao: Noise-Aware Super-Resolution of Depth Maps Via Graph-Based Plug-And-Play Framework. ICIP 2018: 2536-2540 [9] Zhaohui Che, Guangtao Zhai, Ke Gu, Patrick Le Callet, Xianming Liu, Deming Zhai, Xiao Gu: Adaptive Screen Content Image Enhancement Strategy using Layer-based Segmentation. ISCAS 2018: 1-5 [10] Rong Chen, Deming Zhai, Xianming Liu, Debin Zhao: Color-Guided Depth Map Super-Resolution via Joint Graph Laplacian and Gradient Consistency Regularization. MMSP 2018: 1-5 [11] Deming Zhai, Ao Li, Yang Li, Yang Liu, GuoJun Liu, Xianming Liu, Maozu Guo: Discrete Manifold-Regularized Collaborative Filtering for Large-Scale Recommender Systems. PCM 2018: 513-523 2017 [1] Xianming Liu, Gene Cheung, Xiaolin Wu, Debin Zhao: Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding of JPEG Images. IEEE Trans. Image Process. 26(2): 509-524 (2017) [2] Xianming Liu, Deming Zhai, Jiantao Zhou, Shiqi Wang, Debin Zhao, Huijun Gao: Sparsity-Based Image Error Concealment via Adaptive Dual Dictionary Learning and Regularization. IEEE Trans. Image Process. 26(2): 782-796 (2017) [3] Yutao Liu, Ke Gu, Guangtao Zhai, Xianming Liu, Debin Zhao, Wen Gao: Quality assessment for real out-of-focus blurred images. J. Vis. Commun. Image Represent. 46: 70-80 (2017) [4] Shiqi Wang, Xinfeng Zhang, Xianming Liu, Jian Zhang, Siwei Ma, Wen Gao: Utility-Driven Adaptive Preprocessing for Screen Content Video Compression. IEEE Trans. Multimedia 19(3): 660-667 (2017) [5] Yihui Feng, Xianming Liu, Yongbing Zhang, Qionghai Dai: Single depth image super-resolution and denoising based on sparse graphs via structure tensor. ICIP 2017: 4063-4067 [6] Wei Sun, Guangtao Zhai, Xiongkuo Min, Yutao Liu, Siwei Ma, Jing Liu, Jiantao Zhou, Xianming Liu: Dynamic backlight scaling considering ambient luminance for mobile energy saving. ICME 2017: 25-30 [7] Wenbo Zhao, Xianming Liu, Shiqi Wang, Debin Zhao: Multi-scale Similarity Enhanced Guided Normal Filtering. PCM 2017: 645-653 Before 2017 [1] Xianming Liu, Deming Zhai, Jiantao Zhou, Xinfeng Zhang, Debin Zhao, Wen Gao, ``Compressive Sampling based Image Coding for Resource-Deficient Visual Communication,” IEEE Transactions on Image Processing, Vol. 25 , No. 6, pp. 2844-2855，June 2016 (Regular paper). [2] Xianming Liu, Xiaolin Wu, Jiantao Zhou, Debin Zhao, ``Data-driven Soft Decoding of Compressed Images in Dual Transform-Pixel Domain,” IEEE Transactions on Image Processing, Vol. 25 , No. 4, pp. 1649-1659，April 2016 (Regular paper). [3] Xianming Liu, Debin Zhao, Jiantao Zhou, Wen Gao and Huifang Sun, "Image Interpolation via Graph-based Bayesian Label Propagation, IEEE Transactions on Image Processing, Vol. 23, No. 3, pp. 1084-1096, March 2014 (Regular paper). [4] Xianming Liu, Deming Zhai, Debin Zhao, Guangtao Zhai, Wen Gao, " Progressive Image Denoising through Hybrid Graph Laplacian Regularization: A Unified Framework," IEEE Transactions on Image Processing, Vol. 23, No. 4, pp. 1491-1503, April 2014 (Regular paper). [5] Xianming Liu, Debin Zhao, Ruiqin Xiong, Siwei Ma, Wen Gao and Huifang Sun, ``Image Interpolation via Regularized Local Linear Regression, IEEE Transactions on Image Processing, Vol. 20, No. 12, pp. 3455-3469, Dec. 2011 (Regular paper). [6] Xianming Liu, Xiaolin Wu, Jiantao Zhou, Debin Zhao, ``Data-driven Sparsity-based Restoration of JPEG-compressed Images in Dual Transform-Pixel Domain,” CVPR 2015: 5171-5178 [7] Xianming Liu, Xinwei Gao, Debin Zhao, Jiantao Zhou, Guangtao Zhai, Wen Gao, "Model-based Low Bit-rate Video Coding for Resource-deficient Wireless Visual Communication," Neurocomputing, Vol. 162, pp. 180-190, 2015. [8] Xianming Liu, Xiaolin Wu, Debin Zhao, ``Multiple Description Image Coding using Local Random Measurements, in Proceedings of IEEE Data Compression Conference, DCC2014, Snowbird, Utah, USA, Mar.26-28, 2014 (Full paper, Top Conference in Data Compression). · [9] Xianming Liu, Deming Zhai, Debin Zhao, Wen Gao, ``Image Super-Resolution via Hierarchical and Collaborative Sparse Representation, in Proceedings of IEEE Data Compression Conference, DCC2013, Snowbird, Utah, USA, Mar.20-22, 2013 (Full paper, Top Conference in Data Compression, nominated as ``best student paper candidate). · [10] Xianming Liu, Deming Zhai, Guangtao Zhai, Debin Zhao, Ruiqin Xiong, Wen Gao, ``Multi-scale Spatial Error Concealment via Hybrid Bayesian Regression, in Proceedings of IEEE Data Compression Conference, DCC2012, Snowbird, Utah, USA, Apr.12-15, 2012 (Full paper, Top Conference in Data Compression). · [11] Xianming Liu, Debin Zhao, Ruiqin Xiong, Siwei Ma, Wen Gao and Huifang Sun, ``Transductive Regression with Local and Global Consistency for Image Super-Resolution, in Proceedings of IEEE Data Compression Conference, DCC2011, Snowbird, Utah, USA, Mar.29-31, 2011 (Full paper, Top Conference in Data Compression). [12] Xinfeng Zhang, Weisi Lin, Ruiqin Xiong, Xianming Liu, Siwei Ma and Wen Gao,"Low-Rank Decomposition Based Restoration of Compressed Images via Adaptive Noise Esitmation," IEEE Transactions on Image Processing, Vol. 25, No. 9, pp. 4158-4171, Sept. 2016 (Regular paper). [13] Jiantao Zhou, Xianming Liu, O. C. Au, and Y. Y. Tang, “Designing an Efficient Image Encryption-then-Compression System via Prediction Error Clustering and Random Permutation,” IEEE Transactions on Information Forensics and Security, Vol. 9, No. 2, pp. 39-50, 2014 (Regular paper). [14] Jiantao Zhou, O. C. Au, Guangtao Zhai, Y. Y. Tang, Xianming Liu, “ Scalable Compression of Stream Cipher Encrypted Images through Context-Adaptive Sampling,” IEEE Transactions on Information Forensics and Security, Vol. 9, No. 11, pp. 1857-1868, 2014 (Regular paper). [15] Yuanman Li, Jiantao Zhou, An Cheng, Xianming Liu, Yuan Y. Tang, “SIFT Keypoint Removal and Injection via Convex Relaxation”, IEEE Transactions on Information Forensics and Security, Vol. 11, No. 8, pp. 1722 -1735, Aug. 2016 (Regular paper). [16] Jiantao Zhou, Weiwei Sun, Li Dong, Xianming Liu, O. C. Au, Y. Y. Tang, “Secure Reversible Image Data Hiding over Encrypted Domain via Key Modulation,” IEEE Transactions on Circuit and Systems for Video Technology, Vol. 26, No. 3, pp. 441-452, March 2016 (Regular paper). · [17] Shiqi Wang, Ke Gu, Siwei Ma, Weisi Lin, Xianming Liu, Wen Gao, “Guided Image Contrast Enhancement Based on Retrieved Images in Cloud,” IEEE Transactions on Multimedia, Vol. 18, No. 2, pp. 219-232, Feb. 2016 (Regular paper). Group 名称 在读博士生： 2018级：潘金旺（协助赵德斌教授指导） 2019级：庞博，周雄 (腾讯奖学金，国家奖学金)，王瀚章（协助高文院士指导），季发虎（协助高文院士指导） 2020级：张飞龙，林诗昳 2021级：徐家雷，付吉灿，拜子琦（鹏城国家实验室联合培养） 2022级：肖钰儒，张国庆，刘建，李兵（协助指导），王凯（协助指导），李大鑫（协助指导） 2023级：王嘉良 在读硕士生： 2022级: 魏庆彬，张雨桐 2023级: 孙显熠，赵逸凡，刘嘉阳，赵隽娆，秦辰，马健翔 ------------------------------------------------------------------------ 博士毕业生： 2023届：仲志伟（腾讯奖学金，黑龙江省优秀毕业生，哈工大优秀博士毕业生，毕业去向：香港） 2023届：李强 (国家奖学金，哈工大优秀博士毕业生，毕业去向：加拿大) 硕士毕业生： 2023届：武磊（拼多多），刘程飞（奥迪），钟亦奇（哈工大优秀硕士论文，国家奖学金，CVPR一作，华为） 2022届：王凯（读博），沈斯娴（微软），杨栩（AAAI共一，美团），邵通（ACMMM一作，寒武纪） 2021届：孙赫（国家奖学金，哈工大优秀硕士论文，Intel中国研究院），贾玉强（快手），闫纪良（哈工大优秀毕业生，拼多多） 2020届：赵永森（哈工大优秀毕业生，云从科技），韩凯歌（阿里），王晨阳（国家奖学金，哈工大优秀硕士论文金奖，读博），石瑞枫（华为杭研所），王水介（中国移动研究院），沈沾健（百度） 2019届：左文祥（网易游戏） 2018届：陈蓉（哈工大优秀硕士论文银奖，百度），韩驰（新浪微博） 本科实习生： 2018级：刘帅（加拿大阿尔伯特大学硕士全奖）