实验室成员
Lab Member
您所在的位置：首页>教师团队>教授

颜庆义

教授

智能视觉信息处理与通信实验室

knngan@ee.cuhk.edu.hk

English Version
个人简介:

    颜庆义教授曾在香港中文大学、新加坡南洋理工大学和澳大利亚西澳大学担任讲座教授，也曾在澳大利亚莫纳什大学(Monash University)和新加坡国立大学任教。同时还担任过美国两大知名研究机构--AT&T贝尔实验室和贝尔通信研究所的常驻顾问。颜庆义教授先后被中国、澳大利亚和东南亚多所高校聘请为名誉教授和客座教授。

    颜庆义教授的研究领域包括视频信号处理，图像视频编码，多媒体通信等，取得了大量创新性的研究成果。出版英文专著3部，编著7部，学术期刊专刊9部，先后在国内外一些著名的刊物和会议上发表论文400余篇，论文被国内外同行引用8000余次（Google Scholar数据），SCI引用3000余次。获授权美国专利9项，欧洲专利1项，加拿大专利1项，中国专利2项。颜庆义教授担任了多个国际期刊的区域编辑，包括IEEE Transactions on Circuits and Systems for Video Technology, Elsevier国际期刊Journal on Visual Communications and Image Representation，欧洲信号处理协会主办的国际期刊Signal Processing: Image Communication及Journal of Applied Signal Processing。先后担任了包括2010年IEEE图像处理国际会议在内的多个著名的图像和视频处理国际会议主席和联合主席，被聘请为许多专业机构的顾问和技术委员。 

    由于在视觉信息处理理论与应用领域的突出贡献，2000 年被美国电子电气工程师学会评选为IEEE Fellow，1998年被澳大利亚工程师学会评选为IEAust Fellow，1997年被英国电气工程师学会评选为IET Fellow，并当选为2006-2007年度IEEE电路与系统协会杰出讲座学者。 


论文成果:
  • 1.Haoran Wei, Qingbo Wu, Hui Li, King Ngi Ngan, Hongliang Li, and Fanman Meng,”Single Image Dehazing via Artificial Multiple Shots and Multidimensional Context” 2020 IEEE International Conference on Image Processing (ICIP). (Accepted)
  • 2.H. Li, Q. Wu, K. N. Ngan, H. Li and F. Meng, "Region Adaptive Two-Shot Network For Single Image Dehazing," IEEE International Conference on Multimedia and Expo (ICME), London, United Kingdom, 2020, pp. 1-6.
  • 3.Q. Wu, L. Wang, K. N. Ngan, H. Li, F. Meng and L. Xu, "Subjective and Objective De-raining Quality Assessment Towards Authentic Rain Image," in IEEE Transactions on Circuits and Systems for Video Technology, in press, 2020.
  • 4.H. Li, Q. Wu, H. Wei, K. N. Ngan, H. Li, F. Meng, L. Xu, “Haze-robust Image Understanding via Context-Aware Deep Feature Refinement”, IEEE International Workshop on Multimedia Signal Processing (MMSP), Tampere, Finland, 2020, pp. 1-6.
  • 5.Q. Wu, L. Chen, K. N. Ngan, H. Li, F. Meng, L. Xu, “A Unified Single Image De-raining Model via Region Adaptive Coupled Network”, IEEE Visual Communication and Image Processing Conference (VCIP), Macao, 2020, pp. 1-4.
  • 6.Heqian Qiu, Hongliang Li, Qingbo Wu, Fanman Meng, Linfeng Xu, King Ngi Ngan and Hengcan Shi, "Hierarchical Context Features Embedding for Object Detection," in IEEE Transactions on Multimedia, doi: 10.1109/TMM.2020.2971175.
  • 7.Heqian Qiu, Hongliang Li, Qingbo Wu, Fanman Meng, Hengcan Shi, Taijin Zhao and King Ngi Ngan, “Language-Aware Fine-Grained Object Representation for Referring Expression Comprehension” Proceedings of the 28th ACM International Conference on Multimedia, 4171-4180.
  • 8.F Meng, K Huang, H Li, S Chen, Q Wu, KN Ngan, “Hierarchical class grouping with orthogonal constraint for class activation map generation”, Neural Computing and Applications, 1-10, 2020
  • 9.H Shi, H Li, Q Wu, KN Ngan, “Query Reconstruction Network for Referring Expression Image Segmentation”, IEEE Transactions on Multimedia,1,2020
  • 10.Qishang Cheng, Hongliang Li, Qingbo Wu, King Ngi Ngan, “Hybrid-loss supervision for deep neural network”, Neurocomputing, 2020 388(5):78-89.
  • 11.Qishang Cheng, Hongliang Li, Qingbo Wu, Lei Ma, King Ngi Ngan, “Parametric Deformable Exponential Linear Units for deep neural networks”, Neural Networks,2020,125(5):281-289.
  • 12.Qishang Cheng, Hongliang Li, Qingbo Wu, Fanman Meng, Linfeng Xu, King Ngi Ngan, “Learn to Pay Attention Via Switchable Attention for Image Recognition”, IEEE International Conferenceon Multimedia Information Processing and Retrieval (MIPR). Shenzhen, China, August, 6-8, 2020.
  • 13.Xiaoyu Chen, Hongliang Li, Qingbo Wu, King Ngi Ngan, Linfeng Xu, “High-Quality R-CNN Object Detection Using Multi-Path Detection Calibration Network”, IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2020.2987465.
  • 14.Longrong Yang, Hongliang Li, Qingbo Wu, Fanman Meng, and King Ngi Ngan, "Mono is Enough: Instance Segmentation from Single Annotated Sample," 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP).
  • 15.L Ma, H Li, F Meng, Q Wu, KN Ngan,” Discriminative deep metric learning for asymmetric discrete hashing”, Neurocomputing 380, 115-124,4 ,2020
  • 16.Li Wei ，Li Hongliang，Wu Qingbo，Chen Xiaoyu，Ngan King Ngi，“Simultaneously Detecting and Counting Dense Vehicles from Drone Images”IEEE Transactions on Industrial Electronics, pp.1-1，February 2019. [PDF] [PROJECT]
  • 17.Li Wei，Li Hongliang，Wu Qingbo，Meng Fanman，Xu Linfeng，Ngan King Ngi，“HeadNet: An End-to-end Adaptive Relational Network for Head Detection”IEEE Transactions on Circuits and Systems for Video Technology, pp.1-1， 02 January 2019. [PDF]
  • 18.Yuwei Yang, Fanman Meng, Hongliang Li, King N.Ngan and Qingbo Wu, “A New Few-shot Segmentation Network Based on Class Representation” in 2019 IEEE International Conference on Visual Communications and Image Processing.
  • 19.Kaixu Huang, Fanman Meng, Hongliang Li, Shuai Chen, Qingbo Wu and King N.Ngan, “Class Activation Map generation by Multiple Level Class Grouping and Orthogonal Constraint” in 2019 International Conference on Digital Image Computing Techniques and Applications.
  • 20.Ma L, Li H, Meng F, Wu Q, Ngan K N ,”Discriminative Deep Metric Learning for Asymmetric Discrete Hashing”[J]. Neurocomputing, 2019.
  • 21.Qingbo Wu, Lei Wang,King N. Ngan, Hongliang Li,Fanman Meng,” Beyond Synthetic Data: A Blind Deraining Quality Assessment Metric Towards Authentic Rain Image” 2019 IEEE International Conference on Image Processing (ICIP). IEEE, 2019: 2364-2368.
  • 22.Wu Qingbo,Ma Rui,Ngan King Ngi,Li Hongliang,Meng Fanman,” Blind Image Sharpness Assessment And Enhancement via Deep Auxiliary Learning” 2019 IEEE International Conference on Multimedia and Expo (ICME), 2019: 1852-1857.
  • 23.Heqian Qiu, Hongliang Li,Qingbo Wu,Fanman Meng,King Ngi Ngan,Hengcan Shi,” A2RMNet: Adaptively Aspect Ratio Multi-Scale Network for Object Detection in Remote Sensing Images”, Remote Sensing, Vol.11(13), p.1594, 01 July 2019.
  • 24.Qingbo Wu, Hongliang Li, Fanman Meng, and King N. Ngan, "A Perceptually Weighted Rank Correlation Indicator for Objective Image Quality Assessment", IEEE Transactions on Image Processing, vol. 27, no. 5, pp. 2499 - 2513, May 2018. [PDF] [CODE]
  • 25.Qingbo Wu, Hongliang Li, Fanman Meng, and King N. Ngan, "Towards A Blind Quality Metric for Temporally Distorted Streaming Video", IEEE Transactions on Broadcasting, vol. 64, no. 2, pp. 367 - 378, June 2018. [PDF] [CODE]
  • 26.Hengcan Shi, Hongliang Li, Fanman Meng, Qingbo Wu, Linfeng Xu, King N. Ngan, "Hierarchical Parsing Net: Semantic Scene Parsing from Global Scene to Objects", IEEE Transactions on Multimedia, vol. 20, no. 10, pp. 2670 - 2682, 2018.
  • 27.Qingbo Wu, Hongliang Li, King N. Ngan, and Kede Ma, “Blind Image Quality Assessment Using Local Consistency Aware Retriever and Uncertainty Aware Evaluator”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no.9, pp. 2078 - 2089, Sep. 2018. [PDF]
  • 28.Bing Luo, Hongliang Li ; Fanman Meng ; Qingbo Wu ; King Ngi Ngan, “An Unsupervised Method to Extract Video Object via Complexity Awareness and Object Local Parts”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no.7, pp. 1580 - 1594, July 2018.
  • 29.Qingbo Wu, Hongliang Li, Fanman Meng, and King N. Ngan, “Generic Proposal Evaluator: A Lazy Learning Strategy Towards Blind Proposal Quality Assessment”, IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 1, pp. 306-319, Jan. 2018. [PDF] [CODE]
  • 30.Fanman Meng, Hongliang Li, Qingbo Wu, and King Ngi Ngan, “Seeds based Part Segmentation by Seeds Propagation and Region Convexity Decomposition”, IEEE Transactions on Multimedia, vol. 20, no. 2, pp. 310-322, Feb. 2018.
  • 31.Fanman Meng, Hongliang Li, Qingbo Wu, Bing Luo, Chao Huang, and King Ngi Ngan, “Globally Measuring the Similarity of Superpixels by Binary Edge Maps for Superpixel Clustering”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no.4, pp. 906-919, Apr. 2018.
  • 32.Hengcan Shi, Hongliang Li, Qingbo Wu, Fanman Meng, and King Ngi Ngan, “Boosting scene parsing performance via reliable scale prediction,” 26th ACM international conference on Multimedia. Seoul, Korea, October 22 - 26, 2018.
  • 33.Fanman Meng, Hongliang Li, Qingbo Wu, Bing Luo, and King Ngi Ngan, "Weakly Supervised Part Proposal Segmentation from Multiple Images", IEEE Transactions on Image Processing, vol. 26, no. 8, pp. 4019-4031, 2017. [PDF]
  • 34.Yichi Zhang, King Ngi Ngan, Lin Ma and Hongliang Li, “Objective Quality Assessment of Image Retargeting by Incorporating Subjective Quality Measures and Inconsistency Detection”, IEEE Transactions on Image Processing, vol. 26, no. 12, pp. 5980-5993, December 2017.
  • 35.Lei Ma, Hongliang Li, Fanman Meng, Qingbo Wu, King Ngi Ngan, “Learning Efficient Binary Codes From High-Level Feature Representations for Multilabel Image Retrieval”, IEEE Transactions on Multimedia, vol. 19, no. 11, pp. 2545-2560, November 2017.
  • 36.Qingbo Wu, Hongliang Li, Zhou Wang, Fanman Meng, Bing Luo, Wei Li, and King N. Ngan, “Blind Image Quality Assessment Based on Rank-Order Regularized Regression”, IEEE Transactions on Multimedia, vol. 19, no. 11, pp. 2490-2504, November 2017. [PDF]
  • 37.Fanman Meng, Hongliang Li, Qingbo Wu, Bing Luo, and King Ngi Ngan, “Weakly Supervised Part Proposal Segmentation from Multiple Images”, IEEE Transactions on Image Processing, vol. 26, no. 8, pp. 4019 – 4031, 2017.
  • 38.Wei Li, Hongliang Li, Bing Luo, Hengcan Shi, Qingbo Wu, and King N. Ngan, "Improving Object Proposals with Top-down Cues", Signal Processing: Image Communication, vol. 56, pp. 20–27, Aug. 2017.
  • 39.Qingbo Wu, Hongliang Li, King N. Ngan and Linfeng Xu, "Blind Proposal Quality Assessment via Deep Objectness Representation and Local Linear Regression", IEEE International Conference on Multimedia & Expo (ICME 2017), Hong Kong, China, Jul. 10 - 14, 2017. (Oral) [PDF]
  • 40.Miaohui Wang, K.N. Ngan and Hongliang Li, “Low-delay Rate Control for Consistent Quality Using Distortion-based Lagrange Multiplier,” IEEE Transactions on Image Processing, vol. 25, no. 7, pp. 2943-2955, July 2016
  • 41.Qingbo Wu, Hongliang Li, Fanman Meng, King N. Ngan, Bing Luo, Chao Huang, and Bing Zeng, "Blind Image Quality Assessment Based on Multi-Channel Features Fusion and Label Transfer", IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, no. 3, pp. 425 - 440, 2016.
  • 42.Fanman Meng, Hongliang Li, Qingbo Wu, Bing Luo, Chao Huang, King Ngan "Globally Measuring the Similarity of Superpixels by Binary Edge Maps for Superpixel Clustering ", IEEE Transactions on Circuits and Systems for Video Technology, Accepted, 2016. [PDF] [PROJECT]
  • 43.Qingbo Wu, Hongliang Li, Fanman Meng, King N. Ngan, Bing Luo, Chao Huang, Bing Zeng "Blind Image Quality Assessment Based on Multichannel Feature Fusion and Label Transfer ", IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, no. 3, pp. 425-440, 2016. [PDF] [CODE]
  • 44.Qingbo Wu, Hongliang Li and King N. Ngan, "Q-DNN: A Quality-Aware Deep Neural Network for Blind Assessment of Enhanced Images", IEEE International Conference on Visual Communication and Image Processing (VCIP 2016), Chengdu, China, Nov. 27 - 30, 2016. [PDF]
  • 45.Qingbo Wu, Hongliang Li and King N. Ngan, "GIP: Generic Image Prior for No Reference Image Quality Assessment", The Pacific-Rim Conference on Multimedia (PCM 2016), Xi'an, China, Sep. 15 - 16, 2016. [PDF]
  • 46.Jian Xiong, Hongliang. Li, Fanman. Meng, Qingbo Wu and K.N. Ngan, “Fast HEVC Inter CU Decision based on Latent SAD Estimation”, IEEE Transactions on Multimedia, Vol. 17, no. 12, pp. 2147- 2159, Sep. 2015.
  • 47.R. Shi, K.N. Ngan, S. Li, R. Paramesran and Hongliang Li, “Visual Quality Evaluation of Image Object Segmentation: Subjective Assessment and Objective Measure,” IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5033-5045, December 2015.
  • 48.Qingbo Wu, Hongliang Li, Fanman Meng, King Ngi Ngan, Shuyuan Zhu " No reference image quality assessment metric via multi-domain structural information and piecewise regression", Journal of Visual Communication and Image Representation, Volume 32, October 2015, Pages 205-216. [PDF] [CODE]
  • 49.Qingbo Wu, Hongliang Li, King N. Ngan, Bing Zeng and Moncef Gabbouj, "No Reference Image Quality Metric via Distortion Identification and Multi-Channel Label Transfer", IEEE International Symposium on Circuits and Systems (ISCAS 2014), Melbourne, Australia, Jun. 1 - 5, 2014. [PDF]
  • 50.Fanman Meng, Hongliang Li, KingNgi Ngan,Bing Zeng, Nini Rao "Similar Scene Cosegmentation," IEEE international symposium on circuits and systems (ISCAS 2014), Melbourne, Australia, Jun 1-5, 2014. [CODE]
  • 51.Hongliang Li, Fanman Meng, and King N. Ngan, "Co-Salient Object Detection From Multiple Images", IEEE Transactions on Multimedia, vol. 15, no. 8, pp. 1896-1909, 2013.
  • 52.Fanman Meng, Hongliang Li, King Ngi Ngan, Liaoyuan Zeng, Qingbo Wu, "Feature Adaptive Co-segmentation by Complexity Awareness", IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 4809-4824, 2013. [PDF]
  • 53.Fanman Meng, Hongliang Li, Guanghui Liu and King N. Ngan, "From Logo to Object Segmentation", IEEE Transactions on Multimedia, vol. 15, no. 8, pp. 2186-2197, 2013.
  • 54.Hongliang Li, Fanman Meng, and King N. Ngan, "Co-Salient Object Detection From Multiple Images", IEEE Transactions on Multimedia, vol. 15, no. 8, pp. 1896-1909, 2013. [PROJECT]
  • 55.Fanman Meng, Hongliang Li, Guanghui Liu, and King Ngi Ngan, "Image Co-segmentation by Incorporating Color Reward Strategy and Active Contours Model," IEEE Transactions on Cybernetics, vol. 43, no. 2, pp. 725-737, April 2013. [PDF] [CODE] [PROJECT]
  • 56.Fanman Meng, Hongliang Li, Guanghui Liu, and King Ngi Ngan, "Object Co-segmentation based on Shortest Path Algorithm and Saliency Model," IEEE Transactions on Multimedia, vol.14, no. 5, pp. 1429 -1441, 2012. [PDF] [CODE] [PROJECT]
  • 57.Hongliang Li, Guanghui Liu, and King Ngi Ngan, "Guided Face Cartoon Synthesis," IEEE Transactions on Multimedia, vol. 13, no. 6, pp. 1230-1239, 2011. [PROJECT]
  • 58.Hongliang Li, King Ngi Ngan, "A Co-saliency Model of Image Pairs," IEEE Transactions on Image Processing, vol. 20, no. 12, pp. 3365-3375, 2011. [PDF] [PROJECT]
  • 59.Hongliang Li and K.N. Ngan, “Learning to Extract Focused Object from Low DOF Images,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 21, no. 11, November 2011, pp. 1571-1580. [PROJECT]
  • 60.Hongliang Li, King N. Ngan, and Qiang Liu, “FaceSeg: automatic face segmentation for real-time video”, IEEE Transactions on Multimedia, vol.11, no.1, pp.77-88, 2009.
  • 61.Hongliang Li, King N. Ngan, and Zhenyu Wei, “Fast and efficient method for block edge classification and its application in H.264/AVC video coding”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no.6, pp. 756-768, 2008. [PDF] [CODE] [PROJECT]
  • 62.Hongliang Li, and King N. Ngan, “Unsupervised Video Segmentation with Low Depth of Field”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no.12, pp. 1742-1751, 2007.

    • 招生信息：
    硕士：
    081000 信息与通信工程
    06方向：图像与视频处理
    09方向：机器学习与人工智能
    10方向：信号与信息智能处理
    博士：
    081000 信息与通信工程
    06方向：图像与视频处理
    09方向：机器学习与人工智能
    10方向：信号与信息智能处理


    访问量 8662
    更新时间2020-04-03

    联系方式：

    邮编：611731

    实验室地址：成都市高新区（西区）西源大道2006号

    电子科技大学信息与通信工程学院

    技术支持：成都今网科技

    版权所有 © 智能视觉信息处理与通信实验室, 2018