World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
10044
World Ranking
5356
National Ranking
33

Overview

Minsu Cho is affiliated with Pohang University of Science and Technology in South Korea. The primary field of research is computer science, with a particular focus on subfields such as computer vision and pattern recognition, artificial intelligence, radiology, nuclear medicine and imaging, management information systems, and industrial and manufacturing engineering.

The topics covered extensively in Cho's work include human pose and action recognition, multimodal machine learning applications, advanced image and video retrieval techniques, anomaly detection techniques and applications, domain adaptation and few-shot learning, advanced neural network applications, and video surveillance and tracking methods.

Cho has a significant publication record, having contributed frequently to venues that include:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • BMC Public Health
  • IEEE Security & Privacy

Notable recent papers authored or co-authored by Cho include:

  • "Autoregressive Image Generation using Residual Quantization," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs," 2020, arXiv (Cornell University)
  • "Integrative Few-Shot Learning for Classification and Segmentation," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Detector-Free Weakly Supervised Group Activity Recognition," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Future Transformer for Long-term Action Anticipation," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Cho collaborates frequently with several researchers, including:

  • Suha Kwak
  • Chinmay Hegde
  • Manjin Kim
  • Heeseung Kwon
  • Juhong Min

Best Publications

  • Relational Knowledge Distillation

    Wonpyo Park;Dongju Kim;Yan Lu;Minsu Cho

  • Reweighted random walks for graph matching

    Minsu Cho;Jungmin Lee;Kyoung Mu Lee

  • Proxy Anchor Loss for Deep Metric Learning

    Sungyeon Kim;Dongwon Kim;Minsu Cho;Suha Kwak

  • ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization

    Vadim Kantorov;Maxime Oquab;Minsu Cho;Ivan Laptev

  • Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals

    Minsu Cho;Suha Kwak;Cordelia Schmid;Jean Ponce

  • Local-Global Video-Text Interactions for Temporal Grounding

    Jonghwan Mun;Minsu Cho;Bohyung Han

  • Multi-object Tracking with Quadruplet Convolutional Neural Networks

    Jeany Son;Mooyeol Baek;Minsu Cho;Bohyung Han

  • Hyper-graph matching via reweighted random walks

    Jungmin Lee;Minsu Cho;Kyoung Mu Lee

  • Robust Guided Image Filtering Using Nonconvex Potentials

    Bumsub Ham;Minsu Cho;Jean Ponce

  • Learning Graphs to Match

    Minsu Cho;Karteek Alahari;Jean Ponce

  • Multi-Graph Matching via Affinity Optimization with Graduated Consistency Regularization

    Junchi Yan;Minsu Cho;Hongyuan Zha;Xiaokang Yang

  • Robust image filtering using joint static and dynamic guidance

    Bumsub Ham;Minsu Cho;Jean Ponce

  • SCNet: Learning Semantic Correspondence

    Kai Han;Rafael S. Rezende;Bumsub Ham;Kwan-Yee K. Wong

  • Progressive graph matching: Making a move of graphs via probabilistic voting

    Minsu Cho;Kyoung Mu Lee

  • Feature correspondence and deformable object matching via agglomerative correspondence clustering

    Minsu Cho;Jungmin Lee;Kyoung Mu Lee

  • MotionSqueeze: Neural Motion Feature Learning for Video Understanding

    Heeseung Kwon;Manjin Kim;Suha Kwak;Minsu Cho

  • InstaGAN: Instance-aware Image-to-Image Translation

    Sangwoo Mo;Minsu Cho;Jinwoo Shin

  • Unsupervised Object Discovery and Tracking in Video Collections

    Suha Kwak;Minsu Cho;Ivan Laptev;Jean Ponce

  • Finding Matches in a Haystack: A Max-Pooling Strategy for Graph Matching in the Presence of Outliers

    Minsu Cho;Jian Sun;Olivier Duchenne;Jean Ponce

  • Freeze Discriminator: A Simple Baseline for Fine-tuning GANs.

    Sangwoo Mo;Minsu Cho;Jinwoo Shin

  • Proposal Flow

    Bumsub Ham;Minsu Cho;Cordelia Schmid;Jean Ponce

  • Proposal Flow: Semantic Correspondences from Object Proposals

    Bumsub Ham;Minsu Cho;Cordelia Schmid;Jean Ponce

  • The SD Filter: Robust Image Filtering Using Joint Static and Dynamic Guidance

    Bumsub Ham;Minsu Cho;Jean Ponce;Jean Ponce

Frequent Co-Authors

Jean Ponce
Jean Ponce École Normale Supérieure
Kyoung Mu Lee
Kyoung Mu Lee Seoul National University
Bohyung Han
Bohyung Han Seoul National University
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Ivan Laptev
Ivan Laptev Mohamed bin Zayed University of Artificial Intelligence
Jinwoo Shin
Jinwoo Shin Korea Advanced Institute of Science and Technology
Soumik Sarkar
Soumik Sarkar Iowa State University
Baskar Ganapathysubramanian
Baskar Ganapathysubramanian Iowa State University
Yann LeCun
Yann LeCun Facebook (United States)
Josef Sivic
Josef Sivic Czech Technical University in Prague

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