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About Shijian Lu
Dr Shijian Lu is an Adjunct Associate Professor in the Computer Vision Department at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI).
Biography
Dr. Lu is currently an associate professor (tenured) in the School of Computer Science and Engineering, Nanyang Technological University (NTU). He has held an adjunct position at MBZUAI since late 2021. Before joining NTU in 2017, he took a number of leadership roles in the Institute for Infocomm Research (I2R), Agency for Science, Technology, and Research (A*SATR) in Singapore, including head of the Visual Attention Lab, deputy head of the Satellite Department, co-chair of the Image and Pervasive Access Laboratory (a CNRS overseas laboratory hosted by A*STAR in Singapore).
Lu’s research focuses on computer vision and sensing, image and video analytics, and deep learning. He has been working on scene text detection and recognition for years, contributing to a number of impactful benchmarking datasets as well as innovative detection and recognition techniques. In recent years, Lu has been studying how to tackle data collection and data annotation challenges in deep network training.
Present | Adjunct Associate Professor, Mohamed bin Zayed University of Artificial Intelligence ‐ Department of Computer Vision | |
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Disciplines
Research Interests
Professional Service and Affiliations
2018 - 2021 | Senior Program Committee, AAAI Conference on Artificial Intelligence | 2018 - 2021 | Senior Program Committee, International Joint Conference on Artificial Intelligence | 2019 | Area Chair, 15th International Conference on Document Analysis and Recognition | 2017 - 2018 | Area Chair, IEEE Winter Conference on Applications of Computer Vision | 2017 | Area Chair, 14th IAPR International Conference on Document Analysis and Recognition |
Honors and Awards
- Top winner of the ICFHR2014 Competition on Word Recognition from Historical Documents.
- Top winner of the ICDAR 2013 Robust Reading Competition (1st in the scene text segmentation task).
- Top winner of the ICDAR 2013 Document Image Binarization Contest (DIBCO 2013).
- Top winner of the H-DIBCO 2010 – Handwritten Document Image Binarization Competition.
- Top winner of the ICDAR 2009 Document Image Binarization Contest (DIBCO 2009).