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Peiguang Jing

Peiguang Jing



Tianjin International Engineering Institute




School of Electrical and Information Engineering.


Associate Professor


330 Room, Building 26



Dr. Jing Peiguang, received his Ph.D. in Information and Communication Engineering, from Tianjin University. He is currently an associate professor at the School of Electronic and Information Engineering at Tianjin University.

He and his group at Tianjin University have published more than 50 refereed journal and conference papers. Dr. LIU has been awarded 10 authorized Chinese patents, with another 5 Chinese patents pending.



Associate Professor, School of Electrification and Information Engineering, Tianjin University, Department of Electronic Information Engineering, 2020-Today

Lecturer, School of Electrification and Information Engineering, Tianjin University, Department of Electronic Information Engineering, 2018-2020

Ph.D., National University of Singapore, School of Computer School, 2014-2015

Ph.D., School of Electrical Automation and Information Engineering, Tianjin University,2013-2018


Research Interests

(1) Multimodal short video semantic understanding and analysis

In the context of the rapid development of the micro-video industry, research focuses on the core problem of micro-video semantic analysis, gradually expanding the research from the prediction of the popularity of multimodal micro-videos, the detection of micro-video events, the classification of multimodal micro-videos, and the prediction of micro-video memorability.

(2) Semantic analysis of classic media data

Semantic analysis is a key and difficult problem in high-level cognition in visual understanding. The focus of the research is to solve the semantic gap between low-level visual features and high-level semantic concepts. Currently, research on classic media data represented by images is gradually focusing on high-level abstract semantic concepts. Starting from representation learning, research is conducted in areas such as sentiment analysis of multimedia data, memorability analysis, and compatibility prediction of fashionable multimedia.

(3) Temporal data analysis

The rapid growth of data volume and diverse data types bring new challenges to the development of the multimedia field. In order to better solve the context, temporal smoothness, and higher-order problems in temporal data, through in-depth research on the temporal patterns of data under the framework of tensor decomposition and deep learning, and through adaptive learning, the temporal correlation patterns of data are obtained.


Selected Publications (2019-2021)

(1) Peiguang Jing, Yuechen Shang, Liqiang Nie, Yuting Su*, Jing Liu, Meng Wang. Learning Low-rank Sparse Representations with Robust Relationship Inference for Image Memorability Prediction. IEEE Transactions on Multimedia, 2021, DOI: 10.1109/TMM.2020.3009485.

(2) Peiguang Jing, Yuting Su*, Zhengnan Li, Liqiang Nie. Learning robust affinity graph representation for multi-view clustering. Information Sciences, 2021 544: 155-167.

(3) Peiguang Jing, Jing Zhang, Liqiang Nie, Shu Ye, Jing Liu, Yuting Su*. Tripartite Graph Regularized Latent Low-rank Representation for Fashion Compatibility Prediction.IEEE Transactions on Multimedia, 2021DOI: 10.1109/TMM.2021.3062736

(4) Peiguang Jing, Shu Ye, Liqiang Nie, Jing Liu, Yuting Su*. Low-rank regularized multi-representation learning for fashion compatibility prediction. IEEE Transactions on Multimedia, 2020, 22(6): 1555-1566.

(5) Peiguang Jing, Yuting Su*, Xiao Jin, Chengqian Zhang. High-Order Temporal Correlation Model Learning for Time-Series Prediction. IEEE Transactions on Cybernetics, 2019, 49(6):2385-2397.

(6) Wei Lu, Fugui Fan, Jinghui Chu, Peiguang Jing*, Yuting Su. Wearable Computing for Internet of Things: A Discriminant Approach for Human Activity Recognition. IEEE Internet of Things Journal, 2019, 6(2): 2749-2759.

(7) Peiguang Jing, Yuting Su, Liqiang Nie, Humin Gu, Jing Liu, Meng Wang. A Framework of Joint Low-rank and Sparse Regression for Image Memorability Prediction. IEEE Transactions on Circuits and Systems for Video Technology, 2019,29(5):1296-1309.

(8) Peiguang Jing, Yuting Su, Zhengnan Li, Jing Liu, Liqiang Nie. Low-rank regularized tensor discriminant representation for image set classification. Signal Processing, 2019, 156:62-70.

(9) Jing Liu, Wanning Sun, Yuting Su, Peiguang Jing*, Xiaokang Yang. BE-CALF: bit-depth enhancement by concatenating all level features of DNN, IEEE Transactions on Image Processing, 2019, 28 (10), 4926-4940.

(10) Jing Liu, Pingping Liu, Yuting Su, Peiguang Jing*, Xiaokang Yang. Spatiotemporal Symmetric Convolutional Neural Network for Video Bit-Depth Enhancement, IEEE Transactions on Multimedia, 2019, 21(9),2397-2406.


Teaching Experience

(1) Multimedia data mining and analysis