I²R Staff Profile

Dr Tan Hui Li is a Senior Scientist at the Visual Intelligence Department, A*STAR Institute for Infocomm Research (A*STAR I²R). She has been with A*STAR I²R since 2007, and has worked on various signal processing and multi-media research areas such as music information retrieval, visual quality assessment, and video compression. Under the on-going Collaborative AI project, she is actively working on visual question answering for real-world tasks, and is part of teams that won benchmarking challenges such as EPIC-Kitchens Dataset Action Anticipation, DSTC10 Audio Visual Scene-Aware Dialog (AVSD), and Machine Visual Common Sense (MVCS) STAR Challenge. She also supports various projects on visual defect inspection. She was the PI of a cross-institute project that builds continuous learning platform for visual defect inspection, and is the co-PI of a cross-institute project that investigates natural and adversarial robustness for visual defect inspection. She received her PhD from the Faculty of Engineering, National University of Singapore, in 2017. 

Professional and Academic Engagements

• Vice Chairman, IEEE Singapore, Woman in Engineering Affinity Group (2011-2012)
• Secretary, IEEE Singapore, Woman in Engineering Affinity Group (2017)
• Treasurer, IEEE Singapore, Woman in Engineering Affinity Group (2009-2010, 2014-2015) 
• Committee Member, IEEE Singapore, Women in Engineering Affinity Group (2009-2017)
• Local Arrangement Team Member, Asia-Pacific Signal and Information Processing Annual Summit and Conference (APSIPA ASC) (2010)

Publications
Journal Papers

  • J. Duan, S. Yu, H. L. Tan, H. Zhu, C. Tan, “A survey of embodied AI: From simulators to research tasks,” IEEE Trans. Emerging Topics in Computational Intelligence, 2022.
  • H. L. Tan, H. Zhu, J.-H. Lim, and C. Tan, “A comprehensive survey of procedural video datasets,” Comput. Vis. Image Understanding, 2021.
  • H. L. Tan, C. C. Ko, and S. Rahardja, “Fast coding quad-tree decisions using prediction residuals statistics for High Efficiency Video Coding (HEVC),” IEEE Trans. Broadcast., vol. 62, no. 1, pp. 128-133, Mar. 2016.
  • H. L. Tan, Z. Li, Y. H. Tan, S. Rahardja, and C. Yeo, “A perceptually relevant MSE-based image quality metric,” IEEE Trans. Image Process., vol. 22, no. 11, pp. 4447-4459, Nov. 2013.
  • C. Yeo, H. L. Tan, and Y. H. Tan, “On rate distortion optimization using SSIM,” IEEE Trans. Circuits Syst. Video Technol., vol. 23, no. 7, pp. 1170-1181, Jul. 2013.

Conference Papers

  • X. Huang, H. L. Tan, J. J. Kim, “Comparing Classification and Generation Approaches to Situated Reasoning with Vision-language Pre-trained Models,” MVCS Workshop (ECCV 2022). [Best Performance Award]
  • X. Huang, H. L. Tan, M. C. Leong, L. Li, Y. Sun, R. Jiang, J. J. Kim, “Investigation on Transformer-based Multi-modal Fusion for Audio-Visual Scene-Aware Dialog,” DSTC10 Workshop (AAAI 2022). [Best System for Answer Generation]
  • M. C. Leong, H. L. Tan, H. Zhang, L. Li,  F. Lin, J.-H. Lim, “Joint learning on the hierarchy representation for fine-grained human action recognition,” IEEE Int. Conf. on Image Processing (ICIP), 2021.
  • Q. Xu, N. Gauthier, W. Liang, F. Fang, H. L. Tan, et al., “TAILOR: Teaching with active and incremental learning for object registration,” AAAI Conf. on Artificial Intelligence Workshop, 2021. [Best Demo Award]
  • H. L. Tan, M. C. Leong, Q. Xu, L. Li, et al., “Task-oriented multi-modal question answering for collaborative applications,” IEEE Int. Conf. on Image Processing (ICIP), 2020.
  • J. Duan, S. Yu, H. L. Tan, and C. Tan, “ActioNet: An interactive end-to-end platform for task-based data collection and augmentation in 3D environment,” IEEE Int. Conf. on Image Processing (ICIP), 2020.
  • Y. Sun, Y. Cheng, M. C. Leong, H. L. Tan, K. E. Ak, “Team VI-I2R Technical Report on EPIC-Kitchens Action Anticipation Challenge,” EPIC-Kitchens Challenge Workshop (CVPR), 2020. [Ranked 2nd among global teams]
  • H. L. Tan, K.-T. Ma, H. Zhu, M. Rice, J.-H. Lim, C. Tan, “A survey of procedural video datasets,” IEEE Int. Conf. on Computer Vision Pattern Recognition (CVPR) FIVER Workshop, 2018.
  • H. L. Tan, J. Fan, and S. Lu, “Regions-of-interest extraction from remote sensing imageries using visual attention modelling,” SPIE Image and Signal Processing for Remote Sensing XXII, Sep. 2016.
  • J. Fan, H. L. Tan, and S. Lu, “Multipath sparse coding for scene classification in very high resolution satellite imagery,” SPIE Image and Signal Processing for Remote Sensing XXI, Oct. 2015.
  • H. L. Tan, Y. H. Tan, Z. Li, S. Rahardja, and C. Yeo, “Perceptually relevant energy function for seam carving,” IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2013.
  • H. L. Tan, F. Liu, Y. H. Tan, and C. Yeo, “On fast coding tree block and mode decision for HEVC,” IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), pp. 825-828, 2012.
  • C. Yeo, H. L. Tan, and Y. H. Tan, “Rate distortion optimization using SSIM,” IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), pp. 833-836, 2012.
  • Y. H. Tan, C. Yeo, H. L. Tan, and Z. Li, “On residual quad-tree coding in HEVC,” IEEE Int. Workshop on Multimedia Signal Processing (MMSP), pp. 1-4, 2011.
  • H. L. Tan, Y. Zhu, L. Chaisorn, and S. Rahardja, “Audio onset detection using energy-based and pitch-based processing,” IEEE Int. Symp. on Circuits and Systems (ISCAS), pp. 3689-3692, 2010.

A*STAR celebrates International Women's Day

A*STAR Women In Science

From groundbreaking discoveries to cutting-edge research, our researchers are empowering the next generation of female science, technology, engineering and mathematics (STEM) leaders.

Get inspired by our #WomeninSTEM