Minsu Cho Minsu Cho (조 민수)
Associate Professor
Department of Computer Science and Engineering
Graduate School of Artificial Intelligence
POSTECH (Pohang Univ. of Science and Technology, 포항공과대학교)
77 Cheongam-ro, Nam-gu, Pohang, Gyeongbuk, South Korea 37673

Email: mscho ~at~ postech dot ac dot kr

I am an Associate Professor in the Department of Computer Science and Engineering and Graduate School of Artificial Intelligence at POSTECH, South Korea, leading POSTECH Computer Vision Lab. My research lies in the areas of computer vision and machine learning, especially in the problems of visual semantic correspondence, symmetry analysis, object discovery, action recognition, and minimally-supervised learning. I am interested in the relationship between correspondence, symmetry, and supervision in visual learning.

Before joining POSTECH in the fall of 2016, I was a researcher (Starting Research Position) in the Inria WILLOW team at École Normale Supérieure (ENS), Paris, France, where I have worked with Jean Ponce and Cordelia Schmid. I completed my Ph.D. in 2012, under the supervision of Kyoung Mu Lee at Seoul National University, Seoul, Korea.

I am an Associate Editor of the International Journal of Computer Vision (IJCV) and the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and have been serving an Area Chair in leading conferences including CVPR, ECCV, ICCV, and NeurIPS. In 2020, I have been inducted into the Young Korean Academy of Science and Technology (Y-KAST). In 2023, I was a Visiting Faculty Researcher at Google Research.

POSTECH CV Lab Publications Software Students Teaching CV
Google scholar


NEWS 
  • I will be giving a keynote lecture at the 30th International Workshop on Frontiers of Computer Vision (IW-FCV 2024), Tokyo, Japan.
  • I co-organize the Tool-Augmented VIsion (TAVI) workshop at CVPR 2024.
  • I serve as a Program Chair for KCCV 2024, Busan, Korea, and ACCV 2024, Hanoi, Vietnam.
  • I serve as an Area Chair for CVPR 2024 and ECCV 2024.
  • Our paper, `Efficient Semantic Matching with Hypercolumn Correlation,' was included in the Best Paper Finalists at WACV 2024.
  • Three papers were accepted at WACV 2024.
  • Two papers were accepted at NeurIPS 2023.
  • I returned to POSTECH after my sabbatical year in France.
  • I take a sabbatical year and join Google Research as a Visiting Faculty Researcher.
  • One paper was accepted at ICML 2023.
  • Six papers were accepted at CVPR 2023.
  • Journal extension of our `Convolutional Hough Matching' paper (CVPR 2021 oral) has been accepted at TPAMI 2023.

  • I am an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and International Journal of Computer Vision (IJCV).
  • I served as an Organizing Committee member for ICCV 2023 (Workshop Chair), MVA 2021 (Program Chair), ICCV 2019 (Web Chair), and ACM Multimedia 2018 (Web Chair).
  • I served as an Area Chair / Senior Program Committee member for CVPR 2023, ICCV 2023, MVA 2023, NeurIPS 2023, WACV 2023, AAAI 2022, CVPR 2022, ICPR 2022, NeurIPS 2022, AAAI 2021, BMVC 2021 CVPR 2021, ICCV 2021, IJCAI 2021, CVPR 2020, ICPR 2020, IJCAI-PRICAI 2020, ICCV 2019, ACCV 2018, CVPR 2018, and WACV 2018.



  • RECENT PUBLICATIONS (Click here for a full list)

    Seungwook Kim, Juhong Min, Minsu Cho
    Efficient Semantic Matching with Hypercolumn Correlation (Best Paper Finalist)   
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, Waikoloa, Hawaii.

    Jeongbeen Yoon, Sanghyun Kim, Suha Kwak, Minsu Cho
    Optical Flow Domain Adaptation via Target Style Transfer   
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, Waikoloa, Hawaii.

    Donghyeon Kwon, Minsu Cho, Suha Kwak
    Self-supervised Learning of Semantic Correspondence Using Web Videos   
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, Waikoloa, Hawaii.

    Dayoung Gong*, Joonseok Lee*, Deunsol Jung, Suha Kwak, Minsu Cho
    Activity Grammars for Temporal Action Segmentation   
    Conference on Neural Information Processing Systems (NeurIPS), 2023, New Orleans, USA.

    Doyup Lee, Chiheon Kim, Minsu Cho, Wook-Shin Han
    Locality-Aware Generalizable Implicit Neural Representation   
    Conference on Neural Information Processing Systems (NeurIPS), 2023, New Orleans, USA.

    Seungwook Kim*, Chunghyun Park*, Yoonwoo Jeong, Jaesik Park, Minsu Cho
    Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning    
    International Conference on Machine Learning (ICML), 2023, Honolulu, Hawaii.

    Jongmin Lee, Byungjin Kim, Seungwook Kim, Minsu Cho
    Learning Rotation-Equivariant Features for Visual Correspondence   
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, Vancouver, Canada.

    Dahyun Kang, Piotr Koniusz, Minsu Cho, Naila Murray
    Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification & Segmentation   
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, Vancouver, Canada.

    Deunsol Jung, Sanghyun Kim, Wonhwa Kim, Minsu Cho
    Devil's on the Edges: Selective Quad Attention for Scene Graph Generation   
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, Vancouver, Canada.

    Sanghyun Kim, Deunsol Jung, Minsu Cho
    Relational Context Learning for Human-Object Interaction Detection   
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, Vancouver, Canada.

    Hyolim Kang, Hanjung Kim, Joungbin An, Minsu Cho, Seon Joo Kim
    Soft-Landing Strategy for Alleviating the Task Discrepancy Problem in Temporal Action Localization Tasks   
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, Vancouver, Canada.

    Chiheon Kim, Doyup Lee, Saehoon Kim, Minsu Cho, Wook-Shin Han
    Generalizable Implicit Neural Representations with Instance Pattern Composers   
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, Vancouver, Canada.

    Juhong Min, Seungwook Kim, Minsu Cho
    Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence   
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023, accepted.
    [IEEE Xplore] [project page]




    SOFTWARE CODES & DATASETS
  • SPair-71k Semantic Correspondence Benchmark Dataset (Paper)   
  • Hyperpixel Flow (Paper)   
  • Relational Knowledge Distillation (Paper)   
  • SCNet: Learning Semantic Correspondence (Paper)
  • ContextLocNet: ConvNet for Weakly-Supervised Object Detection (Paper)
  • Region Proposal Matching + Semantic Correspondence Benchmark (Paper, Data)
  • Unsupervised Object Discovery and Localization (Paper)
  • Graph Learning for Matching (Paper, Data)
  • Outlier-Robust Graph Matching (MPM) (Paper)
  • Progressive framework for Boosting Graph Matching Performance (Paper, Code)
  • Robust Graph Matching (RRWM) (Paper) & Hyper-Graph Matching (RRWHM), (Paper)
  • Mode Seeking on Graphs (Paper)
  • Hierarchical Authority-Shift Clustering (Paper)
  • Deformable Object Matching via Correspondence Clustering (Paper)
  • SNU Dataset for Cosegmentation (Paper, Data)


    STUDENTS
    PhD:
  • Deunsol Jung, 2016-
  • Woohyeon Shim, 2016-
  • Ahyun Seo, 2018-
  • Jeongbeen Yoon, 2018-
  • Jongmin Lee, 2018-
  • Juhong Min, 2018-
  • Manjin Kim, 2019-
  • Sanghyun Kim, 2019-
  • Dahyun Kang, 2019-
  • Seungwook Kim, 2020-
  • Jinhwi Lee (POSCO), 2019-
  • Yoonwoo Jeong, 2020-
  • Dayoung Kong, 2020-
  • Sangki Kim, 2022-
  • Junha Lee, 2023-
  • Chunghyun Park, 2023-

  • Masters:
  • Seungho Lee, 2019-
  • Yunseon Choi, 2022-
  • Jaejun Hwang, 2022-
  • Min Jung Lee, 2022-
  • Sua Choi, 2022-
  • Eunchan Jo, 2023-
  • Nahyuk Lee, 2023-
  • Sangjin Lee, 2023-

  • Alumni:
  • Jeany Son (GIST), 2018, PhD (co-advised with B. Han)
  • Paul Hongsuck Seo (Korea University), 2020, PhD (co-advised with B. Han)
  • Jonghwan Mun (KakaoBrain), 2020, PhD (co-advised with B. Han)
  • Dongju Kim (NVIDIA), 2019, Master
  • Wonpyo Park (Google), 2019, Master
  • Kihyun You (Lunit), 2020 at POSTECH
  • Heeseung Kwon (Inria), 2021, PhD
  • Seungkwan Lee (Deeping Source), 2021, Master
  • Hyunsoo Chung (Spacewalk), 2021 at POSTECH
  • Ilchae Jung (NAVER Clova), 2022, PhD (co-advised with B. Han)
  • Jungtaek Kim (Pittsburgh University), 2022, PhD (co-advised with S. Choi)
  • Byungjin Kim (SAMSUNG), 2023, Master
  • Joonseok Lee, 2023, Master

  • Hector Dang-Nhu (ENS Paris), 2019, Intern at POSTECH
  • Pierre Jobic (ENS Cachan), 2018, Intern at POSTECH
  • Matthieu Toulemont (Ecole des Ponts Paristech), 2018, Intern at POSTECH
  • Idil Kanpolat (co-advised with E. Konukoglu, ETH Zurich), 2017, Intern at POSTECH
  • Kai Han (co-advised with J. Ponce, ENS), 2016, Intern at Inria Paris
  • Sergiu Irimie (co-advised with J. Ponce, ENS), 2016, Intern at Inria Paris
  • Yumin Suh (co-advised with J. Ponce, ENS), 2015, Intern at Inria Paris

  • TEACHING
    2023 Fall: Automata and Formal Languages (at POSTECH CSE)
    2022 Spring: Automata and Formal Languages (at POSTECH CSE)
    2022 Spring: Arficial Intelligence and Data Science (at POSTECH CSE/AIGS)
    2021 Fall: Automata and Formal Languages (at POSTECH CSE)
    2021 Spring: Arficial Intelligence and Data Science (at POSTECH CSE/AIGS)
    2021 Spring: Language and Vision (at POSTECH CSE/AIGS)
    2020 Fall: Automata and Formal Languages (at POSTECH CSE)
    2020 Spring: Deep Learning (at POSTECH CSE/AIGS)
    2020 Spring: Arficial Intelligence and Data Science (at POSTECH CSE/AIGS)
    2019 Fall: Introduction to Deep Learning (at POSTECH CSE)
    2019 Spring: Language and Vision (at POSTECH CSE)
    2018 Fall: Automata and Formal Languages (at POSTECH CSE)
    2018 Spring: Language and Vision (at POSTECH CSE)
    2017 Fall: Automata and Formal Languages (at POSTECH CSE)
    2017 Spring: Language and Vision (at POSTECH CSE)
    2016 Fall: Introduction to Computer Vision (at POSTECH CSE)