Scholar
Minsu Cho
Google Scholar ID: 5TyoF5QAAAAJ
Mu-Eun-Jae Endowed Chair Professor, Associate Professor of CSE & AI, POSTECH
Computer Vision
Machine Learning
Graph Matching
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Citations & Impact
All-time
Citations
10,982
H-index
50
i10-index
97
Publications
20
Co-authors
121
list available
Contact
CV
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Publications
7 items
Cog3DMap: Multi-View Vision-Language Reasoning with 3D Cognitive Maps
2026
Cited
0
Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards
2026
Cited
0
Space-Time Forecasting of Dynamic Scenes with Motion-aware Gaussian Grouping
2026
Cited
0
Vision-aligned Latent Reasoning for Multi-modal Large Language Model
2026
Cited
0
MV-SAM: Multi-view Promptable Segmentation using Pointmap Guidance
2026
Cited
0
DextER: Language-driven Dexterous Grasp Generation with Embodied Reasoning
2026
Cited
0
Affostruction: 3D Affordance Grounding with Generative Reconstruction
2026
Cited
0
Resume (English only)
Academic Achievements
Associate Editor for International Journal of Computer Vision (IJCV) and IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Served as Area Chair / Senior Program Committee member for leading conferences including CVPR, ECCV, ICCV, and NeurIPS over many years
Inducted into the Young Korean Academy of Science and Technology (Y-KAST) in 2020
Appointed Mu-Eun-Jae Endowed Chair Professor at POSTECH in 2024
Recipient of the KCCV Sang Uk Lee Prize at KCCV 2024
Program Chair for KCCV 2024 and ACCV 2024; Workshop Chair for ICCV 2023; held various organizational roles in major conferences since 2018
Published extensively at top venues: e.g., 4 papers at CVPR 2025, 4 at ICCV 2025 (including 2 highlights), 5 at ECCV 2024, 2 at NeurIPS 2024, etc.
Paper on efficient semantic matching was a Best Paper Finalist at WACV 2024
Published on memory-modular learning in TMLR, sorting networks at ICLR 2024, and 3D shape assembly at ICML 2024
Background
Mu-Eun-Jae (無垠齋) Endowed Chair Professor and Associate Professor at POSTECH (Pohang University of Science and Technology), South Korea
Affiliated with the Department of Computer Science and Engineering and the Graduate School of Artificial Intelligence
Leads the POSTECH Computer Vision Lab
Research focuses on computer vision and machine learning, particularly visual semantic correspondence, symmetry analysis, object discovery, action recognition, and minimally-supervised learning
Interested in the interplay among correspondence, symmetry, and supervision in visual learning
Co-authors
121 total
Suha Kwak
POSTECH
Juhong Min
Samsung Research America
Jean Ponce
Ecole Normale Superieure/PSL Research University
Kyoung Mu Lee
Professor, Department of Electrical and Computer Engineering, Seoul National University
Jaesik Park
Seoul National University, CSE & IPAI
Cordelia Schmid
Research director INRIA
Co-author 7
Seungwook Kim
PhD Candidate, POSTECH (Pohang University of Science and Technology) / Research Intern @ Bytedance
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