Junsuk Choe
Assistant Professor @ Department of Computer Science and Engineering,
(Affiliated) Assistant Professor @ Department of Artificial Intelligence, Sogang University,
(Affiliated) Chair @ Data Science and AI Major, Graduate School of Information & Technology,
Office: AS-913
Email: jschoe at sogang dot ac dot kr
Google Scholar / CV / Github / Calendar
I am an Assistant Professor in the Department of Computer Science and Engineering at Sogang University. Before joining Sogang University in Fall 2021, I spent two wonderful years as a Research Intern and then a Research Scientist at NAVER AI Lab, where I had the good fortune to work with Dongyoon Han, Sangdoo Yun, Seong Joon Oh, Sanghyuk Chun, Byeongho Heo, and Jung-Woo Ha. I obtained my Ph.D. from the Yonsei University in 2020 under the supervision of Prof. Hyunjung Shim, and my B.S. also from the Yonsei University in 2013.
For prospective students/members: We have two openings for the Integrated MS/PhD program. The start date can be flexible. Please contact me via email if you are interested.
News
8/2024: Dongjun received the NRF Fellowship for PhD students (20,000,000 KRW) from the National Research Foundation of Korea.
8/2024: Dongjun is at CMU as a visiting student, supported by the IITP AI Intensive Education Program.
7/2024: Hyoseo started her research internship at NAVER AI Lab.
4/2024: Granted the Outstanding Young Scientist Grant (900,000,000 KRW) as a PI from the National Research Foundation of Korea.
4/2024: 1 paper accepted to Pattern Recognition Letters (IF: 5.1)
12/2023: Received the Sogang College of Engineering Young Fellow Award.
12/2023: 1 paper accepted to AAAI 2024
8/2023: 1 paper accepted to WACV 2024
7/2023: 1 paper accepted to ICCV 2023
7/2023: Junsuk, Minyoung, and Hyoseo served as visiting scholars at the Tübingen AI Center
3/2023: 1 paper accepted to Pattern Recognition Letters (IF: 4.757)
10/2022: Received the Sogang College of Engineering Outstanding Lecture Award. link
4/2022: 1 paper accepted to PAMI (IF:24.314)
2/2022: 1 paper accepted to CVPR 2022
9/2021: Joined the Dept. of CSE at Sogang University as an Assistant Professor.
7/2021: 4 papers accepted to ICCV 2021
6/2021 : Recognized as an outstanding reviewer by CVPR 2021
3/2021: 1 paper accepted to PR (IF:7.196)
2/2021: 1 paper accepted to CVPR 2021
5/2020: 1 paper accepted to PAMI (IF: 17.861)
2/2020: 1 paper accepted to CVPR 2020
7/2019: 1 paper accepted to ICCV 2019 (oral presentation)
3/2019: 1 paper accepted to CVPR 2019 (oral presentation)
In 2018: 1 paper accepted to Information Sciences (IF: 5.524)
Research Interests
Data-centric Machine Learning highlights the significance of high-quality, well-labeled data over complex models. My work specifically targets enhancing model performance through better data preprocessing, augmentation, and labeling. By prioritizing data management, I aim to close the gap between theoretical models and practical applications.
Machine Learning with Minimal Supervision aims to efficiently use both labeled and unlabeled data to improve model performance while reducing the need for extensive manual labeling. Specifically, I am interested in weakly-supervised learning, which leverages weakly-labeled data, and continual learning, which enables models to learn and adapt over time without forgetting previous knowledge.
Trustworthy Machine Learning focuses on ensuring model reliability and transparency, which are crucial for developing robust and accountable AI systems. Specifically, I am working on machine unlearning to enable models to forget specific data points from their training set, thereby ensuring compliance with data privacy regulations and improving model adaptability. Additionally, I am focusing on uncertainty estimation to quantify the confidence of model predictions, providing insight into the reliability of the outputs and guiding decision-making processes
Lab Members
Dongjun Hwang (PhD student, 24.03-)
Doyeol Baek (MS student, 22.09-)
Minyoung Lee (MS student, 23.03-)
Hyoseo Kim (Integrated MS PhD student, 22.09-)
Yeji Park (Integrated MS PhD student, 23.03-)
Yejin Kim (MS student, 24.03-)
Alumni
Sung-hwan Han (BS student, 23.01-24.06)
Dongjun Hwang (MS student, 22.03-24.02) → PhD student at Sogang CSE
Junyong Kang (BS student, 21.12-23.03) → MS student at KAIST AI
Teaching
CSE6517: Special Topics in Representation Learning (Graduate, Fall 2024)
CSE6528: Bigdata Computing Capstone Design (Graduate, Fall 2024)
CSE4014: Introduction to Deep Learning (Undergraduate, Fall 2024)
COR1010: Basic Artificial Intelligence Programming (Undergraduate, Spring 2024)
CSE4130: Fundamentals of Machine Learning (Undergraduate, Spring 2024)
CSE6100: Deep Learning (Graduate, Spring 2024)
GITA388: Fundamentals of Deep Learning (Graduate, Spring 2024)
GITA388: Pattern Recognition (Graduate, Spring 2024)
CSE5321: Fundamentals of Natural Language Processing (Undergraduate+Graduate, Fall 2023)
CSE6517: Special Topics in Representation Learning (Graduate, Fall 2023)
CSE6528: Bigdata Computing Capstone Design Graduate, (Graduate, Fall 2023)
GITA388: Pattern Recognition (Graduate, Fall 2023)
CSE3080: Data Structure (Undergraduate, Spring 2023)
CSE4130: Fundamentals of Machine Learning (Undergraduate, Spring 2023)
GITA388: Fundamentals of Deep Learning (Graduate, Spring 2023)
CSE4120: Fundamentals of Compiler Construction (Undergraduate, Fall 2022)
CSE6528: Bigdata Computing Capstone Design (Graduate, Fall 2022)
CSE2003: Computer Programming I (Undergraduate, Spring 2022)
CSE3080: Data Structure (Undergraduate, Spring 2022)
CSE4120: Fundamentals of Compiler Construction (Undergraduate, Fall 2021)
CSE3015: Introduction to Digital Circuits (Undergraduate, Fall 2021)
Submissions
Anonymous Title
Minyoung Lee, Kyungwoo Song, Junsuk Choe.
Submitted to Neural Information Processing Systems.
Anonymous Title
Jeongsoo Kim, Jongho Nang, Junsuk Choe.
Submitted to Neural Information Processing Systems.
Improved Semantic Segmentation by Fisheye Image Augmentation for Driving Scene
Hyeseong Lee, Sunmin Park, Miyoung Lee, Junsuk Choe, Sungwon Jung.
Submitted to Pattern Recognition Letters.
Curriculum Learning with Class-label Composition for Weakly Supervised Semantic Segmentation
Dongjun Hwang, Hyoseo Kim, Doyeol Baek, Hyunbin Kim, Inhye Kye, Junsuk Choe.
Submitted to Pattern Recognition.
Improving ViT Interpretability with Patch-level Mask Prediction
Junyong Kang, Byeongho Heo, Junsuk Choe.
Submitted to Pattern Recognition Letters (Under Revision).
Forecasting Effective Label Types for Weakly-supervised Semantic Segmentation
Minhyun Lee*, Kyungmin Kim*, Junsuk Choe, Hyunjung Shim. (* indicates equal contribution)
Submitted to International Journal of Computer Vision.
Small Object Matters in Weakly Supervised Object Localization
Dongjun Hwang, Seong Joon Oh, Junsuk Choe.
Submitted to Pattern Recognition.
Discovering an Inference Recipe for Weakly-Supervised Object Localization
Sanghuk Lee*, Cheolhyun Mun*, Youngjung Uh, Junsuk Choe, Hyeran Byun. (* indicates equal contribution)
Submitted to Pattern Recognition (Under Revision).
Selected Publications (2019-)
Weakly-supervised Incremental learning for Semantic segmentation with Class Hierarchy
Hyoseo Kim, Junsuk Choe.
Pattern Recognition Letters, 2024. (IF: 5.1)
[journal]
Weakly Supervised Semantic Segmentation for Driving Scenes
Dongseob Kim*, Seungho Lee*, Junsuk Choe, Hyunjung Shim. (* indicates equal contribution)
AAAI Conference on Artificial Intelligence (AAAI), 2024.
[arxiv]
Small Objects Matters in Weakly-supervised Semantic Segmentation
Cheolhyun Mun*, Sanghuk Lee*, Youngjung Uh, Junsuk Choe, Hyeran Byun. (* indicates equal contribution)
IEEE Winter Conference on Applications of Computer Vision (WACV) , 2024.
Neglected Free Lunch - Learning Image Classifiers Using Annotation Byproducts
Dongyoon Han*, Junsuk Choe*, Seonghyeok Chun, John Chung, Minsuk Chang, Sangdoo Yun, Jean Song, Seong Joon Oh. (* indicates equal contribution)
International Conference on Computer Vision (ICCV), 2023.
Entropy Regularization for Weakly Supervised Object Localization
Dongjun Hwang, Jung-Woo Ha, Hyunjung Shim, Junsuk Choe.
Pattern Recognition Letters, 2023. (IF: 4.757)
[journal]
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets
Junsuk Choe*, Seong Joon Oh*, Sanghyuk Chun, Seungho Lee, Zeynep Akata, Hyunjung Shim. (* indicates equal contribution)
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023. (IF: 24.314)
Weakly Supervised Semantic Segmentation using Out-of-Distribution Data
Jungbeom Lee, Seong Joon Oh, Sangdoo Yun, Junsuk Choe, Eunji Kim, Sungroh Yoon.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
Attention-based Dropout Layer for Weakly Supervised Single Object Localization and Semantic Segmentation
Junsuk Choe*, Seungho Lee*, and Hyunjung Shim. (* indicates equal contribution)
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2021. (IF: 24.314)
Keep CALM and Improve Visual Feature Attribution
Jae Myung Kim*, Junsuk Choe*, Zeynep Akata, Seong Joon Oh. (* indicates equal contribution)
International Conference on Computer Vision (ICCV), 2021.
Normalization Matters in Weakly Supervised Object Localization
Jeesoo Kim, Junsuk Choe, Sangdoo Yun, Nojun Kwak.
International Conference on Computer Vision (ICCV), 2021.
Contrastive Attention Maps for Self-supervised Co-localization
Minsong Ki, Youngjung Uh, Junsuk Choe, Hyeran Byun.
International Conference on Computer Vision (ICCV), 2021.
[pdf] [code]
Rethinking Spatial Dimensions of Vision Transformers
Byeongho Heo, Sangdoo Yun, Dongyoon Han, Sanghyuk Chun, Junsuk Choe, Seong Joon Oh.
International Conference on Computer Vision (ICCV), 2021.
Region-based Dropout with Attention Prior for Weakly Supervised Object Localization
Junsuk Choe, Dongyoon Han, Sangdoo Yun, Jung-Woo Ha, Seong Joon Oh, Hyunjung Shim.
Pattern Recognition (PR), 2021. (IF: 7.196)
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
Sangdoo Yun, Seong Joon Oh, Byeongho Heo, Dongyoon Han, Junsuk Choe, Sanghyuk Chun.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Evaluating Weakly Supervised Object Localization Methods Right
Junsuk Choe*, Seong Joon Oh*, Seungho Lee, Sanghyuk Chun, Zeynep Akata, Hyunjung Shim. (* indicates equal contribution)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, Youngjoon Yoo.
International Conference on Computer Vision (ICCV), 2019. (Oral presentation)
Attention-based Dropout Layer for Weakly Supervised Object Localization
Junsuk Choe, and Hyunjung Shim.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (Oral presentation)