I am an Assistant Professor in the Department of Computer Science and Engineering and the College of BioMedical Convergence Engineering at Pusan National University. My research focuses on computer vision, deep learning, and artificial intelligence.
Contact
- Email: srjeonn@pusan.ac.kr
- Office: Room 6507, Building 6 (Computer Engineering Building), 2, Busandaehak-ro 63beon-gil, Geumjeong-gu, Busan, KOREA
Notes for Prospective Students
The PNU Computer Vision Lab researches various topics in computer vision and machine learning, including object recognition, re-identification, and super-resolution. We focus on next-generation AI technologies, such as AutoML, Network Compression, and Artificial General Intelligence (AGI), bridging theoretical research with practical applications. We seek self-motivated students with long-term goals. Graduate applicants (Master’s, Ph.D., Integrated) and interns should specify their participation details and meet prerequisites in Data Structures, AI, Linear Algebra, and Probability & Statistics. Required documents include a Statement of Purpose, CV, and Academic Transcripts.
Education
- PhD, School of Electrical and Electronic Engineering, Yonsei University (Mar. 2016 - Feb. 2022)
- BS, School of Electrical and Electronic Engineering, Yonsei University (Mar. 2009 - Feb. 2016)
Work Experience
- Assistant Professor, Department of CSE, PNU (Aug. 2021 - Present)
- Postdoctoral Scholar, Department of EECS, UC Berkeley (Mar. 2022 - 2023)
- Research Intern, Creative Intelligence Lab, Adobe (May. 2021 - Aug. 2021)
- Research Assistant, Department of EEEN, Yonsei University (Mar. 2016 - Feb. 2022)
Other PNU Affiliations
- PNU AI Research Center
- PNU Industry-Academia Collaboration Foundation
- PNU Graduate Program in Computer Vision
Professional Services
- Local Arrangements Chair - KCCV 2024
Publications
2023
- Local-guided Global: Paired Similarity Representation for Visual Reinforcement Learning
Hyesong Choi, Hunsang Lee, Wonil Song, Sangryul Jeon, Dongbo Min, Kwanghoon Sohn
CVPR 2023
2022
- Pyramidal Semantic Correspondence Networks
Sangryul Jeon, Seungryong Kim, Dongbo Min, Kwanghoon Sohn
TPAMI 2022 - COAT: Correspondence-driven Object Appearance Transfer
Sangryul Jeon, Seungryong Kim, Dongbo Min, Kwanghoon Sohn
BMVC 2022 (Spotlight presentation) / TPAMI 2022 - Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence
Sunghwan Hong, Jisu Nam, Seokju Cho, Susung Hong, Sangryul Jeon, Dongbo Min, Seungryong Kim
NeurIPS 2022 - Unsupervised Scene Sketch to Photo Synthesis
Jiayun Wang, Sangryul Jeon, Stella X. Yu, Xi Zhang, Himanshu Arora, Yu Lou
ECCV Workshop 2022 - AIM: Advances in Image Manipulation workshop and challenges
2021
- CATs: Cost Aggregation Transformers for Visual Correspondence
Seokju Cho, Sunghwan Hong, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, Seungryong Kim
NeurIPS 2021 - Dense Semantic Correspondence
Sangryul Jeon, Dongbo Min, Seungryong Kim, Kwanghoon Sohn, Dohyun Kim, Jungtae Lee, Jangsup Moon, Taesup Moon
CVPR 2021
2020
- Guided Semantic Flow
Sangryul Jeon, Dongbo Min, Seungryong Kim, Kwanghoon Sohn
ECCV 2020
2019
- Joint Learning of Semantic Alignment and Object Landmark Detection
Sangryul Jeon, Dongbo Min, Seungryong Kim, Kwanghoon Sohn
ICCV 2019 - Semantic Attribute Matching Networks
Seungryong Kim, Dongbo Min, Somi Jeong, Sunok Kim, Sangryul Jeon, Kwanghoon Sohn
CVPR 2019
2018
- Recurrent Transformer Networks for Semantic Correspondence
Seungryong Kim, Stephen Lin, Sangryul Jeon, Dongbo Min, Kwanghoon Sohn
NeurIPS 2018 (Spotlight presentation) - PARN: Pyramidal Affine Regression Networks for Dense Semantic Correspondence
Sangryul Jeon, Seungryong Kim, Dongbo Min, Kwanghoon Sohn
ECCV 2018
2017
- FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence
Seungryong Kim, Dongbo Min, Bumsub Ham, Sangryul Jeon, Stephen Lin, Kwanghoon Sohn
CVPR 2017