Addison Lin Wang

Addison Lin Wang is an Assistant Professor in the Artificial Intelligence (AI) Thrust of Information Hub and an Affiliate Assistant Professor in the Department of Computer Science and Engineering, the Hong Kong University of Science and Technology (HKUST). I am leadning Visual Learning and Intelligent Systems (VLIS) LAB @ HKUST, GZ Campus.
I was a Postdoc researcher in the visual intelligence(VI) lab at KAIST from August to Decemeber, 2021. I finished my Ph.D. degree in VI Lab at KAIST, supervised by Prof. Kuk-Jin Yoon from KAIST and advised by Prof. Tae-Kyun Kim from Imperial College London. In the three years of my Ph.D. study on computer vision and AI for intelligent systems, I had collaborated with my friend Dr. Mohammad Mostafavi from GIST, Korea. I also had a chance to work with Prof. Sung-Eui Yoon from the School of Computing at KAIST. Before August 2018, I was a Ph.D. candidate in the Dept. of Industrial & Systems Eng. and School of Computing at KAIST.
I am working on computer vision, computational photography, deep learning, MR/AR for intelligent systems. I am leading research on computer vision with Neuropmorphic/Thermal/360 cameras, Computer vision for AR/VR, Adverse vision problems, and Deep learning methods for intelligent mobile sytems.
He has also been working with Prof. Yishan Shen on the security problems of smart city and Prof. Lik-hang Lee on the metaverse for city-human interaction.

I am currently looking for well-motivated graduate students, research intern or posdoc researchers to join my group. If you are interested in our research, please reach out to me via email by sending your CV and research statement (mandatory).
Those accepted students and researchers will be well paid. We aim to make leading research on the fields of novel camera-based computer vision, computational imaging, efficient deep learning methods, and computer vision-supported AR/MR/metaverse for intelligent mobile systems.
Currently, the addimission for PhD/Mphil is still ongoing, please check the HKUST Guangzhou Pilot Scheme.


I am not often updating my personal page, recent updates can be found in our lab homepage.

Research Interests

Computer Vision, Computational Photography, Deep Learning, Intelligent Systems

  • Neuromorphic camera-based vision.
  • Thermal camera-based vision.
  • Ominidirectional camera-based vision.
  • Vision in all seasons for intelligent systems.
  • Computational imaging and low-level vision problems.
  • 3D vision and pixel-level segmentation for intelligent systems.
  • Transfer learning, semi-/self-supervised learning, GANs for visual learning.
  • Adversarial attack and robustness for intelligent systems.
  • Computer vision for AR/VR/Metaverse.

Work Experiences

  • 2018/03 to 2018.08

    Research Assistant @ AIM Lab, CS Dept., KAIST

  • 2021/08 to 2021/12

    Postdoc Researcher @ VI Lab, ME Dept., KAIST

  • 2021/12 to Now

    Assistant Professor @ AI Thrust, Information Hub, HKUST
    Affiliate Assistant Professor @ Computer Science and Eng., HKUST

Education Background

  • Bechalor (2010-2014)

    Mechanical Eng. & Automation

    Harbin Engineering Univ.

  • Master (2015-2017)

    ME (AR/VR for Engineering)

    Korea Advanced Institute of Science & Technology (KAIST)

  • Ph.D. (2017-2021)

    IE,CS and ME (Artificial Intelligence)

    Korea Advanced Institute of Science & Technology (KAIST)

Publications (Selected International Conferences and Journals)

We strive to publish the most cutting-edge research on top-tier conferences and journals in computer vision and AI.

  1. (Submitted) SphereSR: 360° Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representation,
    Youngho Yoon, Wang, Lin, Inchul Chung and Kuk-Jin Yoon
    IEEE Conference
  2. (Submitted) BIPS: Bi-modal Indoor Panorama Synthesis via Residual Depth-aided Adversarial Learning,
    Changgyoon Oh, Wonjune Cho, Daehee Park, Yujeong Chae, Wang, Lin and Kuk-Jin Yoon
    IEEE Conference
  3. (Submitted) Event-guided Deblurring of Unknown Exposure Time Videos,
    Tae-Woo Kim, Jeong-Min Lee, Wang, Lin, and Kuk-Jin Yoon
    IEEE Conference
  4. (Submitted) All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda,
    Lik-Hang Lee, Tristan Braud*, Pengyuan Zhou*, Wang, Lin*, Dianlei Xu*, Zijun Lin*, Abhishek Kumar, Carlos Bermejo, Pan Hui (* co-second author),
    Proceedings of the IEEE (IF: 10.961)
  5. (Submitted) SiamEvent: Event-based Object Tracking via Edge-aware Similarity Learning with Siamese Networks,
    Yujeong Chae, Wang, Lin and Kuk-Jin Yoon
    IEEE Robotics and Automation Letters (RA-L), 2022, International Conference on Robotics and Automation, ICRA, 2022
  6. Dual Transfer Learning for Event-based End-task Prediction via Pluggable Event to Image Translation,
    Wang, Lin, Yujeong Chae and Kuk-Jin Yoon
    International Conference on Computer Vision, ICCV, 2021 (Q1 conference)
  7. Deep Learning for HDR Imaging: State-of-the-Art and Future Trends,
    Wang, Lin and Kuk-Jin Yoon
    IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI, 2021 (IF: 17.861, rank: 2/266, 1/136)
  8. Semi-supervised Student-Teacher Learning for Single Image Super-Resolution,
    Wang, Lin and Kuk-Jin Yoon
    Pattern Recognition Journal, 2021 (IF: 7.74, rank: 17/140, 20/273)
  9. Joint Intensity Image Reconstruction and Super-Resolution with an Even Camera
    Wang, Lin, Tae-Kyun Kim, and Kuk-Jin Yoon
    IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI (IF: 17.861, rank: 2/266,1/136)
  10. PSAT-GAN: Efficient Adversarial Attacks against Holistic Scene Understanding via End-to-End Partially Shared GANs,
    Wang, Lin and Kuk-Jin Yoon
    IEEE Transactions on Image Processing, TIP, 2021 (IF: 10.856, rank: 11/266, 8/136)
  11. EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Crossmodal Knowledge Distillation,
    Wang, Lin, Yujeong Chae, Sunghoon, Yoon, Tae-Kyun Kim and Kuk-Jin Yoon
    IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2021 (Q1 conference)
  12. GraphShop: Graph-based Approach for Shop-type Recommendation
    Guoyuan An, Sungeui Yoon, Jaeyoon Kim, Wang, Lin*, Myoungho Kim
    SIAM International Conference on Data Mining, 2021 (Q1 conference)
  13. Knowledge distillation and student-teacher learning for visual intelligence: A review and new outlooks,
    Wang, Lin and Kuk-Jin Yoon,
    IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI, 2021 (IF: 17.861, rank: 2/266, 1/136)
  14. Learning to Reconstruct HDR Images from Events, with Applications to Depth and Flow Prediction,
    Mohammad Mostafavi, Wang, Lin, and Yoon, Kuk-Jin Yoon,
    International Journal of Computer Vision, IJCV, 2021 (IF: 7.410, rank: 17/136)
  15. EventSR: From Asynchronous Events to Image Reconstruction, Restoration, and Super-Resolution via End-to-End Adversarial Learning,
    Wang, Lin, Tae-Kyun Kim, and Kuk-Jin Yoon,
    IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2020 (Q1 conference)
  16. Deceiving Image-to-Image Translation Networks for Autonomous Driving with Adversarial Perturbations,
    Wang, Lin, Wonjune Cho, and Kuk-Jin Yoon
    IEEE Robotics and Automation Letters (RA-L), 2020 International Conference on Robotics and Automation, ICRA, 2020 (Q1 conference in robotics)
  17. Event-based high dynamic range image and very high frame rate video generation using conditional generative adversarial networks,
    Wang, Lin*, Mohammad Mostafavi*, and Kuk-Jin Yoon,
    IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2019 (Q1 conference)
  18. Co-DesignMR: A MR-based Interactive Workstation Design System Supporting Collaboration,
    Wang, Lin, and Kuk-Jin Yoon,
    arXiv preprint arXiv:1907.03107, 2019
  19. Visual simulation of a capsizing ship in stormy weather condition,
    Wang, Lin, Soonhung Han,
    Visual Computer 35, 1855–1868, 2019 (IF: 2.601, rank: 39/108)
  20. A visual simulation of ocean floating wind power system,
    Wang, Lin, Hyuncheol Kim, Imgyu Kim, and Soonhung Han,
    Computer Animation and Virtual Worlds 30, no. 2, 2019 (IF: 1.020)

Teaching Experiences

I have been teaching and mentoring students as TA or mentor.

  • AIAA 5027: 2022 Deep Learning for Visual Intelligence: Trends and Challenges
  • AIAA 6101: AI Thrust Seminar
  • AIAA 6102: AI Thrust Seminar
  • 2021 -- Research advisor (with Prof. Yiran Shen) @ Shandong Univ., (2 Master’s student)
  • 2021 -- Research Assistant (student mentoring) @ VI Lab, KAIST, (3 Ph.D. students and 1 Master’s student)
  • 2020 -- Research mentoring @ SGCR Lab, School of Computing
  • 2020 -- Samsung NPEX Course, Teaching Assistant.
  • 2019 -- ME495: Undergraduate Research Program (URP), Teaching Assistant.
  • 2018 -- IE490: Undergraduate Research Program (URP), Teaching Assistant.
  • 2017 -- IE312: Introduction to Human Factors Engineering, Teaching Assistant.

Academic Services

I have been serving the reserach community as reviewers (sensior community members) for many top-tier conferences and journals.

  • Techncial Program Chair, MetaBuild Workshop, 29th IEEE Virtual Reality and 3D User Interfaces Conference (IEEE VR 2022)
  • International Conference on Computer Vision and Pattern Recognition
  • International Conference on Computer Vision
  • International Conference on Robotics and Automation
  • International Conference on Neural Information Processing Systems
  • IEEE Robotics and Automation Letters (RA-L)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Intelligent Transportation Systems (long-term reviewer)
  • IEEE Transactions on Image Processing (TIP)
  • IET Computer Vision
  • Journal of Computers & Graphics
  • IEEE/CAA Journal of Automatica Sinica (Invited guest specialist)
  • Association for the Advancement of Artificial Intelligence (AAAI)
  • ACM Transactions on Knowledge Discovery from Data
  • Visual Computing for Industry, Biomedicine, and Art
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • Signal Processing Letters

Invited Talks

I have been invited to give talks in several places in my Postdoc and PhD study.

  • 2022 -- HKUST CMA Thrust Seminar (invited speaker)
  • 2022 -- USTC-HKUST Metaverse Workshop (invited speaker)
  • 2021 -- HKUST, Information Hub, AI Thrust Seminar (invited speaker)
  • 2021 -- EE Department @ Yonsei Univ. Korea (invited talk)
  • 2021 -- EE Department @ UNIST, Korea (invited talk)
  • 2021 -- CVPR 2021 Doctoral Consortium
  • 2021 -- KCCV 2021 Doctoral Consortium
  • 2020 -- Samsung Electronics (project talk)
  • 2019 -- NAVER Labs (project talk)
  • 2019 -- International Workshop on Robust Computer Vision (IWRCV)

Honors & Awards

I graduated from my Ph.D with the highest hornor (PhD research award) from ME @ KAIST. I have invited to participate in CVPR 2021 Doctoral Consortium; meanwhile I have also been selected as the outsanding reviewer in CVPR 2021. Here, I list some important hornors and awards.

  • 2021 -- Highest Ph.D. Research Award, Dept. Mechanical Eng., KAIST
  • 2021 -- CVPR 2021 Doctoral Consortium
  • 2021 -- Outstanding Reviewer for CVPR 2021
  • 2021 -- Best paper award in 33th Workshop on Image Processing and Image Understanding (IPIU)
  • 2021 -- Best paper award in 31th Workshop on Image Processing and Image Understanding (IPIU)
  • 2017 -- KAIST scholarship in Ph.D course
  • 2015 -- KAIST scholarship in M.S. course

Projects and Funding

  • 2020/09 to 2021/09 -- Improving image quality via event-based high-speed image processing technology.
  • 2022/01 to 2024/01 -- Robustness of computer vision network models for intelligent mobile systems (in preparation)
  • 2022/08 to 2024/08 -- Big data and AI for smart city management and perception (in preparation)
  • 2022/08 to 2023/08 -- Computer vision and big data for healthcare and sports (in preparation)
  • 2022/05 to 2023/05 -- Combining Events and RGB for 3D Digital Human Modeling (in preparation)
  • 2022/05 to 2023/05 -- Compressed Image/Video Enhancement (in preparation)

Research Colloboration

I focus on a broad collboration with world-wide research groups.

Name Affiliation Email
Prof. Kuk-Jin Yoon Korea Advanced Institute of Science & Technology (KAIST) kjyoon@kaist.ac.kr
Prof. Tae-Kyun Kim Korea Advanced Institute of Science & Technology (KAIST) & Imperial Colledge London kimtaekyun@kaist.ac.kr
Prof. Sung-Eui Yoon Korea Advanced Institute of Science & Technology (KAIST) sungeuiy@kaist.ac.kr
Prof. Soonhung Han Korea Advanced Institute of Science & Technology (KAIST) shhan@kaist.ac.kr
Prof. Yishan Shen Shandong University yiran.shen@sdu.edu.cn
Prof. Lik-hang Lee KAIST likhang.lee@kaist.ac.kr
Prof. Boxin Shi Peking University shiboxin@pek.edu.cn
Prof. Wenming Yan Tsinghua University yang.wenming@sz.tsinghua.edu.cn
Prof. Hui Xiong HKUST xionghui@ust.hk
Prof. Hao Liu HKUST liuh@ust.hk
Prof. Lichao Sun Lehigh University lis221@lehigh.edu
Prof. Pengyuan Zhou University of Science and Technology of China pyzhou@ustc.edu.cn
Prof. Pan HUI HKUST panhui@ust.hk