|Academic Profile |
| || |
Prof Cai Jianfei
Professor, School of Computer Science and Engineering
Phone: +65 67906150
Office: N4 02A 26
|Jianfei received his PhD degree from the University of Missouri-Columbia. He is currently a Professor and Cluster Deputy Director of NTU Data Science & AI Research center (DSAIR) and Associate Director of NTU ROSE Lab. He has served as the Head of Visual & Interactive Computing Division and the Head of Computer Communication Division at NTU. His major research interests include computer vision, multimedia and deep learning. He has published over 200 technical papers in international conferences and journals. He is a co-recipient of paper awards in ACCV, IEEE ICIP and MMSP. He has served as the leading Technical Program Chair for IEEE International Conference on Multimedia & Expo (ICME) 2012. He is currently an Associate Editor for IEEE Trans on Multimedia (TMM) and has served as an Associate Editor for IEEE Trans on Image Processing (T-IP) during 2013-2017 and for IEEE Trans on Circuits and Systems for Video Technology (T-CSVT) during 2007-2013. He has also served as the Chair for IEEE CAS Visual Signal Processing and Communication Technical Committee (VSPC-TC) during 2016-2018.|
|Jianfei's major research interests include computer vision, multimedia and deep learning. Currently, he focuses on the cross-discipline research among the areas of computer vision, computer graphics, machine learning and multimedia technologies.|
- Automatic Tagging for Complex Images through Deep Learning
- Cost-Optimal Mobile Computing in the Cloud
- Cross-Layer Design for Video Streaming over Wireless Mesh Networks
- Deep Learning Based Real Time Face Replacement
- Intelligent Semi-automatic Segmentation of Organs and Tumors from CT/MRI Images
- LIDAR, GEOMETRY AND MACHINE FOR VIRTUALIZATION AND SEMANTICS ENRICHMENT OF 3D CITY MODELS
- Making Greater Sense of Big Visual Data: Intelligent Fine-grained Annotation and Analysis
- Network Coding Based Routing Using Fountain Codes for MANETS
- New Local Illumination Model, Fine-grained Shape Recovery and Beyond
- Rapid Rich Object Search (ROSE) Lab
- Semantic 3D labeling & reconstruction with RGB-D data
- Semi-supervised Image Recognition with Attributes and Knowledge Graph
- Toward Joint IT-Thermal Optimization to Improve Energy Efficiency for High-Ambient Temperature Data Centre in the Tropics via Learning-based Algorithms
- Y. Cai, L. Ge, J. Cai and J. Yuan. (2018). Weakly supervised 3D hand pose estimation from monocular RGB images. ECCV.
- Q. Tao, H. Yang, and J. Cai. (2018). Zero-annotation object detection with web knowledge transfer. ECCV.
- J. Gu, J. Cai, J. Shafiq, L. Niu and G. Wang. (2018). Look, imagine and match: improving textual-visual cross-modal retrieval with generative models. CVPR.
- Y. Guo, J. Zhang, J. Cai, B. Jiang and J. Zheng. (2018). CNN-based real-time dense face reconstruction with inverse-rendered photo-realistic face images. IEEE Transactions on Pattern Analysis and Machine Intelligence, in press, 1-14.
- D.Xu, Q.Duan, J.Zheng, J.Zhang, J.Cai, T.J.Cham. (2018). Shading-based Surface Detail Recovery under General Unknown Illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(2), 423 - 436.
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