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Pilhyeon Lee

Ph.D. student

Yonsei University

Biography

I am currently pursuing a PhD degree in Computer Science at Yonsei University, advised by Prof. Hyeran Byun. I visited Microsoft Research Asia as a research intern, working with Dr. Yan Lu and Dr. Jinglu Wang.

My research interests include computer vision, video understanding, and weakly-supervised learning.

I am looking for research groups that I can visit as an intern to collaborate with insightful researchers.

Please feel free to contact me.

Interests

  • Computer Vision
  • Deep Learning
  • Video Understanding
  • Weakly-supervised Learning

Education

  • PhD in Computer Science, 2018-present

    Yonsei University, Korea

  • BSc in Computer Science & Engineering, 2014-2018

    Chung-Ang University, Korea

Recent News

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2021

[2021.08] Our paper on brain computer interface was accepted to ACPR 2021.

[2021.07] Our paper on weakly-supervised temporal action localization was accepted to ICCV 2021 as Oral presentation (3.3% acceptance rate).

[2021.07] Our paper on weakly-supervised temporal action localization got the excellent paper award in the conference of Korean Artificial Intelligence Association.

[2021.07] Our paper on domain generalization was accepted to MM 2021 as Oral presentation (9.2% acceptance rate).

[2021.01] Our paper on face aging was accepted to ICASSP 2021.

[2021.01] Our paper on brain computer interface was accepted to BCI 2021.

2020

[2020.12] Our paper on weakly-supervised temporal action localization was accepted to AAAI 2021.

[2020.11] Our paper on zero-shot action recognition got the best paper award in the joint conference of Microsoft and Korean Artificial Intelligence Association.

[2020.09] Our paper on fairness in AI was accepted to ACCV 2020.

[2020.08] I delivered a presentation on our paper at KCCV 2020.

Publications

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Subject Adaptive EEG‑based Visual Recognition

Learning Action Completeness from Points for Weakly-supervised Temporal Action Localization

Feature Stylization and Domain-aware Contrastive Learning for Domain Generalization

Continuous Face Aging Generative Adversarial Networks

Weakly-supervised Temporal Action Localization by Uncertainty Modeling

Background Suppression Network for Weakly-supervised Temporal Action Localization

Contact

  • lph1114@yonsei.ac.kr
  • +82-2-2123-3876
  • D810, Engineering Hall D, Yonsei-ro 50, Seoul,