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)
Sheng-hua Zhong*, Jianfeng Peng, Peiqi Liu. Question generation based on chat-response conversion. Concurrency and Computation: Practice and Experience, Nov. 2019.
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) [pdf]
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. [pdf]
Sheng-hua Zhong, Yanhong Li, Yan Liu, Zhiqiang Wang*. A computational investigation of learning behaviors in MOOCs. Computer Applications in Engineering Education (CAE), 2017. [pdf]
Songtao Wu, Sheng-hua Zhong*, Yan Liu. Deep residual learning for image steganalysis. Multimedia Tools and Applications (MTAP). Accept. 2017. [pdf]
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. [pdf]
Jiaxin Wu,Sheng-hua Zhong*, Jianmin Jiang, Yunyun Yang. A novel clustering method for static video summarization. Multimedia Tools and Applications. 2016. DOI: 10.1007/s11042-016-3569-x. [pdf]
Sheng-hua Zhong,Yan Liu*, To-Yee Ng, Yang Liu. Perception-oriented video saliency detection via spatio-temporal attention analysis.Neurocomputing . 2016. DOI: http://dx.doi.org/10.1016/j.neucom.2016.04.048 [pdf]
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. [pdf]
Sheng-hua Zhong, Yan Liu*, Qingcai Chen. Visual orientation inhomogeneity based scale-invariant feature transform. Expert Systems with Applications. 42(13), 2015. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
Heeyeon Im,Sheng-hua Zhong, Justin Halberda*. Grouping by proximity and the visual impression of approximate number in random dot arrays, Vision Research.2015. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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 [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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. [pdf]
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) [pdf]
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. [pdf]
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. [pdf]
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). [pdf]
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. [pdf]
