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People

                   

Sheng-hua Zhong

College of Computer Science and Software Engineering                                                                                                
Shen Zhen University                                                                                                
Shen Zhen, GD 518060

Emails:

Education:      

 Ph.D

 M. Eng

 B. Eng

 

Department of Computing, The Hong Kong Polytechinic University

Institution of Information Engineering, Shen Zhen University

Institution of Optical Information Science and Technology, Nanjing University of Posts and Telecommunications

2013

2008

2005

 

Research interests:      

Brain science, cognitive science, visual cortex modeling, deep learning, attention, memory and learning, computational modeling, artificial intelligence, machine learning, multimedia content analysis

Awards:      

 Best Paper Award

 Qualcomm Award

 Women Researcher Award

ACM Intl Conference on Internet Multimedia Computing and Service

ACM Intl Conference on Multimedia

ACM Intl Conference on Internet Multimedia Computing and Service

2011

2011

2010

Professional experience:      

 Postdoctoral Fellowship

 Research Associate

 Visiting Scholar

Johns Hopkins University

The Hong Kong Polytechnic University

Johns Hopkins University

08/2013 – 08/2014

04/2013 – 08/2013

06/2012 – 12/2012

Invited talks:      

Research methodology in brain science.
                               Department of Computer Science
                               Shen Zhen Graduate School, Harbin Institute of Technology
                               Shen Zhen, China.

Computational modeling for vision science.
                               School of Computer Science and Engineering, South China University of Technology
                               Guang Zhou, China.

Video saliency detection via spatio-temporal attention modelling analysis.
                               Department of Computer Science
                               Shen Zhen Graduate School, Harbin Institute of Technology
                               Shen Zhen, China.

Multimedia content analysis via computational human visual model.
                               Department of Psychological & Brain Sciences, Johns Hopkins University
                               Baltimore, Maryland, USA.

Multimedia content analysis via computational human visual cognition.                                
                               Department of Computer Science
                               Shen Zhen Graduate School, Harbin Institute of Technology
                               Shen Zhen, China.

Bilinear deep learning for image classification.
                               Department of Computer Science, City University of Hong Kong
                               Hong Kong, China.

05/2015

 

04/2014

 

05/2013

 

06/2012

 

11/2011

 

08/2011

 


   
Research Grants (Project Leader):      

Merge the Gap in Multimedia Content Understanding via EEG, The Science and Technology Innovation Commission of Shenzhen, No. JCYJ20190808162613130, 300,000 RBM, 2020-2022.

Multimedia Content Analysis based on EEG, The National Science Foundation of Guangdong Province, No. 2016A030310053, 100,000 RMB, 2019-2022.

Visual attention research based on contextual cueing using deep learning framework, The National Natural Science Foundation of China, No. 61502311, 240,000 RMB, 2016-2018.

Shenzhen high-level overseas talents program, 2,700,000 RMB, 2017-2019.

Large scale computational visual attention based on deep learning, The National Science Foundation of Guangdong Province, No. 2016A030310053, 100,000 RMB, 2016-2019.

Visual attention modeling based on contextual cueing, The Science and Technology Innovation Commission of Shenzhen, No. JCYJ20150324141711640, 100,000 RMB, 2015-2017.

NSFC-Guangdong Joint Fund for supercomputing application (Stage II), the National Supercomputing Center in GuangZhou (No. NSFC2015_275)

Tencent “Rhinoceros Birds” - Scientific Research Foundation, 60,000 RMB, 2017-2019

Professional services:      

- Journal Reviewer:

IEEE Transactions on Image Processing
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Multimedia
IEEE Transactions on Sustainable Computing
Multimedia Tools and Applications
Expert Systems with Applications
Journal of the International Measurement Confederation
Neurocomputing
                           

- Conference Technical Program Committee:

ACM Multimedia (MM) 2016, 2018
China Multimedia (China MM) 2018
IEEE International Conference on High Performance Computing and Communications (HPCC) 2018
IEEE International Symposium on Multimedia (ISM) 2016
                           

Graduated Students:      

Phd student in the City University of Hong Kong

Phd student in the Hong Kong Polytechnic University

Wang Fang: Customer value manager in Cigna&CMB

Huang Xinsheng:AI image algorithm engineer in Shenzhen Ruixin Intelligent Medical Technology Co., Ltd.

CMB Network Technology Co., Ltd.

Peng jianfeng:Shenzhen Xinhe Experimental School

Phd student in the Hong Kong Polytechnic University

Lin Jingxu: Development engineer in Alibaba Group

Li Yaoqing: Vision algorithm engineer in Fengtu Technology (Shenzhen) Co., Ltd.

Zhang Beichuan: Recommended algorithm engineer in kuaishou
               

Publications

Journals


    

  • Zhi Zhang, Sheng-hua Zhong*, Ahmed Fares, Yan Liu. Detecting abnormality with separated foreground and background: mutual generative adversarial networks for video abnormal event detection. Computer Vision and Image Understanding (CVIU), 2022.

  • Sheng-hua Zhong, Jingxu Lin*, Jianglin Lu, Ahmed Fares, Tongwei Ren. Deep semantic and attentive network for unsupervised video summarization. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 18(2), Article No: 55, 2022, pp. 1-21.

  • Zhi Zhang, Mingjie Zheng, Sheng-hua Zhong*, Yan Liu. Steganographer detection via similarity accumulation graph convolutional network. Neural Networks (NN), vol. 136, pp. 97-111, 2021.

  • Sheng-hua Zhong, Peiqi Liu, Zhong Ming*, Yan Liu. How to evaluate single-round dialogues like humans: an information-oriented metric. IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), vol. 28, pp. 2211-2223, June 22 2020.

  • Jiaxin Wu, Sheng-hua Zhong*, Yan Liu. Dynamic graph convolutional network for multi-video summarization. Patter Recognition (PR), vol. 107, Nov. 2020.

  • Sheng-hua Zhong, Yuantian Wang, Tongwei Ren*, Mingjie Zheng, Yan Liu, Gangshan Wu. Steganographer detection via multi-scale embedding probability estimation. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 15(4), 103, 2019.

  • Sheng-hua Zhong*, Jianfeng Peng, Peiqi Liu. Question generation based on chat-response conversion. Concurrency and Computation Practice and Experience, e5584, 2019.

  • Sheng-hua Zhong, Yuantian Wang, Tongwei Ren, Mingjie Zheng, Yan Liu, Gangshan Wu. Steganographer detection via multi-scale embedding probability estimation. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 15(4), 103, 2019.

  • Ahmed Fares#, Sheng-hua Zhong#, Jianmin Jiang. EEG-based image classification via a region level stacked bi-directional deep learning framework. In BMC Medical Informatics and Decision Making, vol. 19, No.268, 2019. (# is equally contribution)

  • Songtao Wu, Sheng-hua Zhong*, Yan Liu. A novel convolutional neural network for image steganalysis with shared normalization. IEEE Transactions on Multimedia (TMM), 2019.

  • Mingjie Zheng, Jianmin Jiang, Songtao Wu, Sheng-hua Zhong*, Yan Liu. Content-adaptive selective steganographer detection via embedding probability estimation deep networks, Neurocomputing, Accept, 2019.

  • Sheng-hua Zhong, Xingsheng Huang, Zhijiao Xiao*. Fine-art Painting Classification via Two-channel Dual Path Networks. International Journal of Machine Learning and Cybernetics (JMLC), 2019.

  • Jianmin Jiang, Ahmed Fares, Sheng-hua Zhong*. A context-supported deep learning framework for multimodal brain imaging classification. IEEE Transactions on Human-Machine Systems, 2019.

  • Sheng-hua Zhong#, Jiaxin Wu#, Jianmin Jiang*. Video summarization via spatio-temporal deep architecture. Neurocomputing, Dec. 2018. (# is equally contribution)

  • Jiaxin Wu#, Sheng-hua Zhong#, Zheng Ma, Stephen J. Heinen, Jianmin Jiang*. Foveated convolutional neural networks for video summarization. Multimedia Tools and Applications (MTAP). Accept. 2018.

  • Sheng-hua Zhong, Yanhong Li, Yan Liu, Zhiqiang Wang*. A computational investigation of learning behaviors in MOOCs. Computer Applications in Engineering Education (CAE), 2017.

  • Songtao Wu, Sheng-hua Zhong*, Yan Liu. Deep residual learning for image steganalysis. Multimedia Tools and Applications (MTAP). Accept. 2017.

  • Sheng-hua Zhong, Yan Liu*, Kien A. Hua. Field effect deep networks for image recognition with incomplete data, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 12(4), 2016.

  • Jiaxin Wu,Sheng-hua  Zhong*, Jianmin Jiang, Yunyun Yang. A novel clustering method for static video summarization. Multimedia Tools and Applications. 2016. DOI:

  • Sheng-hua  Zhong,Yan Liu*, To-Yee Ng, Yang Liu. Perception-oriented video saliency detection via spatio-temporal attention analysis.Neurocomputing . 2016. DOI:

  • Sheng-hua  Zhong, Yan Liu*, Bin Li, Jing Long. Query-oriented unsupervised multi-document summarization via deep learning. Expert Systems with Applications. 42(21), 2015.

  • Sheng-hua  Zhong, Yan Liu*, Qingcai Chen. Visual orientation inhomogeneity based scale-invariant feature transform. Expert Systems with Applications. 42(13), 2015.

  • Sheng-hua  Zhong, Zheng Ma, Colin Wilson, Yan Liu, Jonathan I. Flombaum*. Why do people appear not to extrapolate trajectories during multiple object tracking? A computational investigation, 14(12). Journal of Vision (JOV). 2014.

  • Sheng-hua  Zhong, Yan Liu, Yang Liu*, Changsheng Li. Water reflection recognition based on motion blur invariant moments in Curvelet space. IEEE Transactions on Image Processing (TIP). 22(11). 2013.

  • Sheng-hua  Zhong,Yan Liu*, Yang Liu*, Fu-lai Chung. Region level annotation by fuzzy based contextual cueing label propagation. Multimedia Tools and Applications (MTA). 70(2). 2014.

  • Yuantian Wang, Lei Huang, Tongwei Ren, Sheng-hua  Zhong, Han Gu, and Yan Liu. Insights of object proposal evaluation. Multimedia Tools and Applications (MTA). in press.

  • Jing Liu, Tongwei Ren, Yuantian Wang, Sheng-hua  Zhong, Jia Bei, and Shengchao Chen. Object proposal on RGB-D images via elastic edge boxes. Neurocomputing. 70(2). 2014.

  • Yang Liu, Yan Liu*, Sheng-hua  Zhong, and Keith C.C. Chan. Tensor distance based multilinear globality preserving embedding: a unified tensor based dimensionality reduction framework for image and video classification, Expert Systems with Applications (ESWA). 39(12), 2012.

  • Heeyeon Im,Sheng-hua  Zhong, Justin Halberda*.  Grouping by proximity and the visual impression of approximate number in random dot arrays,  Vision Research.2015.

  • Yu Zhao, Yan Liu*, Yang Liu, Sheng-hua  Zhong,Kien A. Hua. Face recognition from a single registered image for conference socializing. Expert Systems with Applications (ESWA). 42(3), 2014.


Conferences

   

  • Yuncong Li, Fang Wang, Sheng-hua Zhong*. “Training entire-space models for target-oriented option words extraction”, Accept in Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022.

  • Fang Wang#, Yuncong Li#, Sheng-hua Zhong*, Cunxiang Yin, Yancheng He. “Aspect-sentiment-multiple-opinion triplet extraction”, in Natural Language Processing and Chinese Computing (NLPCC’21), pp. 583-594, 2021.

  • Zhi Zhang, Sheng-hua Zhong*, Yan Liu. “Video abnormal event detection via context cueing generative adversarial network”, in Proceedings of the IEEE International Conference on Multimedia and Expo (ICME’ 21), pp.1-6, Shenzhen, China, 2021.

  • Yaoqing Li, Sheng-hua Zhong*, Tongwei Ren, Yan Liu. “Fusing CAMs-weighted features and temporal information for robust loop closure detection”, Singapore, pp. 1-7, 2020.

  • Jingxu Lin, Sheng-hua Zhong*, “Bi-directional self-attention with relative positional encoding for vide summarization”, In Proceedings of the IEEE 32thInternational Conference on Tools with Artificial Intelligence (ICTAI’20), pp. 1161-1166, Virtual Conference, 2020.

  • Yuncong Li, Cunxiang Yin, Sheng-hua Zhong*, Xu Pan. Multi-instance Multi-label learning networks for aspect-category sentiment analysis. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP’20), 2020.

  • Yuncong Li, Cunxiang Yin, Sheng-hua Zhong*. Sentence constituent-aware aspect-category sentiment analysis with graph attention networks. In Proceedings of the 9th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC’20), 2020.

  • Yuncong Li, Cunxiang Yin, Sheng-hua Zhong*, Huiqiang Zhong, Jinchang Luo, Siqi Xu and Xiaohui Wu, Better queries for aspect-category sentiment classification. In Proceedings of the 19th China National Conference on Computational Linguistics(CCL’20), 2020.

  • Zhi Zhang, Mingjie Zheng, Sheng-hua Zhong*, Yan Liu. Steganographer detection via enhancement-aware graph convolutional network. In Proceedings of the IEEE International Conference on Multimedia and Expo(ICME’ 20), pp.1-6, 2020.

  • Sheng-hua Zhong, Ahmed Fares, Jianmin Jiang. An attentional-LSTM for improved classification of brain activities evoked by images. In Proceedings of 27th ACM International Conference on Multimedia (ACMMM’ 19), 2019.

  • Jiaxin Wu, Sheng-hua Zhong*, Yan Liu. MvsGCN: A novel graph convolutional network for multi-video summarization. In Proceedings of 27th ACM International Conference on Multimedia (ACMMM’ 19), 2019.

  • Peiqi Liu, Sheng-hua Zhong*, Zhong Ming*, Yan Liu. Information-oriented Evaluation Metric for Dialogue Response Generation Systems. In Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI’18), accept, 2018.

  • Jiaxin Wu, Sheng-hua Zhong, Zheng Ma*, Stephen J. Heinen, Jianmin Jiang. Gaze Aware Deep Learning Model for Video Summarization. In Proceedings of the Pacific-Rim Conference on Multimedia (PCM’18), accept, 2018.

  • Mingjie Zheng, Sheng-hua Zhong*, Songtao Wu, Jianmin Jiang*. Steganographer Detection Based on Multiclass Dilated Residual Networks. In Proceedings of the International Conference on Multimedia Retrieval (ICMR’18), 2018.

  • Dongdong Gui, Sheng-hua Zhong*, Zhong Ming. Implicit affective video tagging using pupillary response. In Proceedings of the International Conference on Multimedia Modeling (MMM’18), 2018.

  • Fang Wang, Sheng-hua Zhong*, Jianfeng Peng, Jianmin Jiang, Yan Liu. Data Augmentation for EEG-based Emotion Recognition with Deep Convolutional Neural Networks. In Proceedings of the International Conference on Multimedia Modeling (MMM’18), 2018.

  • Rong-qin Xu, Sheng-hua Zhong*, Gaoyang Tang, Jiaxin Wu, Yingying Zhu. Adaptive Dehaze Method for Aerial Image Processing. In Proceedings of the Pacific-Rim Symposium on Image and Video Technology (PSIVT’17), 2017.

  • Xingsheng Huang, Sheng-hua Zhong*, Zhijiao Xiao. Fine-art painting classification via two-channel deep residual network. In Proceedings of the Pacific-Rim Conference on Multimedia (PCM’17), 2017.

  • Yuantian Wang, Lei Huang, Tongwei Ren, Sheng-hua Zhong, Yan Liu and Guangshan Wu. Object proposal via depth connectivity constrained grouping. Proceedings of Pacific Rim Conference on Multimedia (PCM’17), 2017.

  • Mingjie Zheng, Sheng-hua Zhong*, Songtao Wu, Jianmin Jiang. Steganographer detection via deep residual network. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME’17), pp. 235-240, 2017.

  • Songtao Wu, Sheng-hua Zhong*, Yan Liu. Residual convolution network based steganalysis with adaptive content suppression. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME’17), pp. 241-246, 2017.

  • Songtao Wu, Sheng-hua Zhong*, Yan Liu. Steganalysis via deep residual network. In Proceedings of the IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS’16), 2016.

  • Su Mei, Shenghua Zhong*, Jianmin Jiang, Transfer learning based on A+ for image super-resolution, accept in 9th International Conference on Knowledge Science, Engineering and Management (KSEM), 2016, pp. 1-12.

  • Sheng-hua Zhong, Jiaxin Wu, Yingying Zhu*, Peiqi Liu, Jiangmin Jiang, Yan Liu, Visual orientation inhomogeneity based on convolutional neural networks, accept in 28th International Conference on Tools with Artificial Intelligence (ICTAI), 2016, pp. 1-8

  • Yingying Zhu, Chuanhua Jiang, Xiaoyan Huang, Zhijiao Xiao,Sheng-hua  Zhong*. A temporal-compress and shorter SIFT research on web videos. In Proceedings of the International Conference on Knowledge Science, Engineering and Management, 2015.

  • Song-tao Wu, Yan Liu*,Sheng-hua  Zhong,Yang Liu. What makes the stego image undetectable? In Proceedings of 7th ACM International Conference on Internet Multimedia Computing and Service (ICIMCS'15), 2015.

  • Sheng-hua  Zhong,Qun-bo Zhang, Zheng-ping Li, Yan Liu*. Motivations and challenges in MOOCs with eastern insights. In Proceedings of International Conference on Education and Management Technology (ICEMT’15), 2015.

  • Jonathan I. Flombaum*,Sheng-hua  Zhong, Bruno Jedynak, Huaibin Jiang. The microgenesis of information acquisition in visual ‘popout’. In Proceedings of the 14th annual meeting of Vision Sciences Society (VSS'15), 2015.

  • Zheng Ma,Sheng-hua  Zhong, Colin Wilson, Jonathan I. Flombaum*. Kalman filter models of multiple-object tracking within an attentional window. In Proceedings of the 14th annual meeting of Vision Sciences Society (VSS'15), 2015.

  • Zhen Yang, Sheng-hua  Zhong,Aaron Carass, Sarah Ying, Jerry L. Prince*. Deep learning for cerebellar ataxia classification and clinical score regression. Accept In The Medical Image Computing and Computer Assisted Intervention (MICCAI'14).

  • Sheng-hua  Zhong,  Zheng Ma, Colin Wilson, Jonathan I. Flombaum*. Kalman filter models of multiple-object tracking within an attentional window. In Proceeding of the 14th annual meeting of Vision Sciences Society (VSS'14), 2014.

  • Hee Yeon Im, Sheng-hua  Zhong, Bruno Jedynak, Lisa Feigenson, Jonathan I. Flombaum*. Information pursuit as a model for efficient visual search. In Proceeding of the 14th annual meeting of Vision Sciences Society (VSS'14),  2014.

  • Sheng-hua  Zhong,Yan Liu*. Video saliency detection via dynamic consistent spatio-temporal attention modelling. In Proceedings of 27th AAAI International Conference on Artificial Intelligence (AAAI’13), 2013.

  • Jonathan I. Flombaum*, Sheng-hua  Zhong,Zheng Ma, Colin Wilson, Yan Liu. What is the marginal advantage of extrapolation during multiple object tracking? Insights from a Kalman filter model. In Proceeding of the 13th annual meeting of Vision Sciences Society (VSS'13), 2013.

  • Hee Yeon Im, Sheng-hua  Zhong, Justin Halberda*. Biases in human number estimation are well-described by clustering algorithms from computer vision. In Proceeding of the 13th annual meeting of Vision Sciences Society (VSS'13), 2013.

  • Sheng-hua  Zhong,Yan Liu*, Gangshan Wu. S-SIFT: A Shorter SIFT without least discriminative visual orientation. In Proceeding of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI’12), 2012.

  • Sheng-hua  Zhong,Yan Liu*, Yao Zhang, Fu-lai Chung. Attention modeling for face recognition via deep learning. In Proceeding of the 34th annual meeting of the Cognitive Science Society (CogSci’12), 2012.

  • Yan Liu, Sheng-hua  Zhong,  Wenjie Li*. Query-oriented multi-document summarization via unsupervised deep learning. In Proceedings of 26th AAAI International Conference on Artificial Intelligence (AAAI’ 12), 2012.

  • Sheng-hua  Zhong,Yan Liu*, Yang Liu. Bilinear deep learning for image classification. In Proceedings of 19th ACM International Conference on Multimedia (SIG MM'11), 2011. (Qualcomm Award)

  • Yang Liu, Yan Liu*,Sheng-hua  Zhong,  Keith C. C. Chan. Semi-supervised manifold ordinal regression for image ranking. In Proceedings of 19th ACM International Conference on Multimedia (SIG MM'11), 2011.

  • Sheng-hua  Zhong, Yan Liu*, Ling Shao, Gangshan Wu. Unsupervised saliency detection based on 2D Gabor and Curvelets transforms. In Proceedings of 3rd ACM International Conference on Internet Multimedia Computing and Service (ACM ICIMCS'11), 2011.

  • Sheng-hua  Zhong, Yan Liu*, Ling Shao, Fu-lai Chung. Water reflection recognition via minimizing reflection cost based on motion blur invariant moments. In Proceedings of 1st ACM International Conference on Multimedia Retrieval (ICMR'11), 2011.

  • Sheng-hua  Zhong,Yan Liu*, Yang Liu, Fu-lai Chung. Fuzzy-based contextual Cueing for region-level annotation. In Proceedings of 2nd ACM International Conference on Internet Multimedia Computing and Service (ACM ICIMCS'10), 2010. (Best Paper Award).

  • Sheng-hua  Zhong,Yan Liu*, Yang Liu, and Fu-lai Chung. A semantic no-reference image sharpness metric based on top-down and bottom-up saliency map modeling. In Proceedings of 17th IEEE International Conference on Image Processing (ICIP'10), 2010.

Lecture

Lecture Zhong File                
Research Institute for Future Media Computing,Shenzhen University 2014 - 2022