Yun-Chun Chen






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About me

I am a first-year Ph.D. student in the Department of Computer Science at the University of Toronto, advised by Animesh Garg. I am also a student researcher at the Vector Institute. I received my Bachelor of Science degree in Electrical Engineering from National Taiwan University in 2018.

My research interests are in the areas of computer vision, robotics, and machine learning. I am particularly interested in transfer learning, meta learning, self-supervised learning, representation learning, video vision, and 3D vision.

Previously, I was fortunate to work with Ming-Hsuan Yang (UC Merced), Jia-Bin Huang (Virginia Tech), Yen-Yu Lin (Academia Sinica), and Winston Hsu (NTU).

If you would like to collaborate, feel free to send me an email.

Info: I am actively looking for a research internship opportunity to work on computer vision and robotics in Summer 2021. Please see my CV for details of my research experience and feel free to reach out to me via email.


News

  • 10 / 2020:   I am serving as a senior program committee for IJCAI 2021.
  • 10 / 2020:   I am serving as a conference reviewer for CVPR 2021 and ICLR 2021.
  • 09 / 2020:   I am serving as a journal reviewer for IEEE Transactions on Image Processing (TIP).
  • 08 / 2020:   I am serving as a program committee for AAAI 2021 and WACV 2021.
  • 08 / 2020:   I am serving as a conference reviewer for CVPR 2020, ECCV 2020, NeurIPS 2020, CoRL 2020, BMVC 2020, and ACCV 2020.
  • 07 / 2020:   Two papers on neural architecture search and meta-learning are accepted to ECCV 2020.
  • 03 / 2020:   One paper on joint semantic matching and object co-segmentation is accepted to PAMI 2020.
  • 09 / 2019:   I am serving as a program committee for AAAI 2020.
  • 07 / 2019:   One paper on cross-resolution generative modeling is accepted to ICCV 2019.
  • 03 / 2019:   I am serving as a conference reviewer for ICCV 2019, BMVC 2019, and ICIP 2019.
  • 02 / 2019:   One paper on unsupervised domain adaptation is accepted to CVPR 2019.
  • 02 / 2019:   One paper on weakly-supervised object localization is accepted to ICASSP 2019.
  • 11 / 2018:   One oral paper on representation learning is accepted to AAAI 2019.
  • 10 / 2018:   We won the Third Place in IEEE Video and Image Processing (VIP) Cup.
  • 07 / 2018:   One paper on semantic matching is accepted to ACCV 2018.

Selected Publications

NAS-DIP: Learning Deep Image Prior with Neural Architecture Search
European Conference on Computer Vision (ECCV), 2020
[Paper] [Project page] [GitHub] [Colab] [Highlight video] [Highlight slides] [Full video] [Full slides]
Learning to Learn in a Semi-Supervised Fashion
European Conference on Computer Vision (ECCV), 2020
[Paper]
Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2020
[Paper] [Project page] [Code] [Slides]
Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond
Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
Major Revision
[Paper]
Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification
IEEE International Conference on Computer Vision (ICCV), 2019
[Paper] [Slides] [Poster]
CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
[Paper] [Project Page] [Code] [Slides] [Poster]
Learning Resolution-Invariant Deep Representations for Person Re-Identification
AAAI Conference on Artificial Intelligence (AAAI), 2019
Oral Presentation
[Paper] [Slides] [Poster]
Deep Semantic Matching with Foreground Detection and Cycle-Consistency
Asian Conference on Computer Vision (ACCV), 2018
[Paper] [Project Page] [Code] [Poster]