Avatar

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. Also, I am collaborating as a visiting researcher with the video understanding team at CLOVA AI Research. In the past, I have 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.

If you are interested in working with me, 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

See more »

2022

[2022.05] Our paper was accepted to Expert Systems With Applications (IF: 6.954).

[2022.05] I will serve as an emergency reviewer for ECCV 2022.

[2022.03] Our paper was accepted to CVPR 2022.

[2022.02] I joined the Clova AI Research, NAVER Corp. as a visiting researcher.

[2022.01] Our paper was accepted to BCI 2022 as Spotlight presentation.

2021

[2021.12] Our paper got the outstanding research paper award from the Graduate School of Yonsei University.

[2021.12] I won the Naver Fellowship Award 2021.

[2021.11] Our paper got the excellent paper award in JKAIA2021.

[2021.10] I was selected as one of the finalists in QIFK 2021 and presented a talk about our paper.

[2021.08] Our paper was accepted to ACPR 2021.

[2021.07] Our paper was accepted to ICCV 2021 as Oral presentation (3.3% acceptance rate).

[2021.07] Our paper got the excellent paper award in CKAIA2021.

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

[2021.01] Our paper was accepted to ICASSP 2021.

[2021.01] Our paper was accepted to BCI 2021 as Spotlight presentation.

Publications

Full list »

Fair Contrastive Learning for Facial Attribute Classification

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

Learning Subject-independent Representation for EEG-based Drowsy Driving Detection

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,