About Me

I am a Ph.D. student at KAIST AI under the supervision of Professor Seungryong Kim. My research interests are broadly in the fields of machine learning and computer vision.
I have been interested in image matching, semi/self-supervised learning, and lately, I have been focusing on large-scale generative models like diffusion models for video, 3D, and neural representations. If you have any questions or are interested in collaborating, please feel free to contact me!

Experience

• Research Intern (Sony AI, Remote)
  • Mar. 2024 - May 2024
• Research Intern (Sony AI, Tokyo, Japan)
  • Dec. 2023 - Mar. 2024
• Visiting Researcher (Queen Mary University of London, UK)
  • Jun. 2023 - Aug. 2023
• Undergraduate Intern (Korea University CVLAB, Seoul, Korea)
  • Jan. 2021 - Feb. 2022
  • Advisor: Prof. Seungryong Kim

Featured Publications

For all publications, please refer here.

International Conferences / Journals

GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping

Junyoung Seo, Kazumi Fukuda, Takashi Shibuya, Takuya Narihira, Naoki Murata, Shoukang Hu, Chieh-Hsin Lai, Seungryong Kim, and Yuki Mitsufuji
Neural Information Processing Systems (NeurIPS), 2024.
[Project] [Link]

Retrieval-Augmented Score Distillation for Text-to-3D Generation

Junyoung Seo*, Susung Hong*, Wooseok Jang*, Hyeonsu Kim, Minseop Kwak, Doyup Lee, and Seungryong Kim
International Conference on Machine Learning (ICML), 2024.
[Project] [Link]

Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation

Junyoung Seo*, Wooseok Jang*, Min-Seop Kwak*, Jaehoon Ko, Hyeonsu Kim, Junho Kim, Jin-Hwa Kim, Jiyoung Lee, and Seungryong Kim
International Conference on Learning Representations (ICLR), 2024.
[Project] [Link]

Depth-Aware Guidance with Self-Estimated Depth Representations of Diffusion Models

Gyeongnyeon Kim, Wooseok Jang, Gyuseong Lee*, Susung Hong, Junyoung Seo, and Seungryong Kim
Pattern Recognition (PR), 2023.

MIDMs: Matching Interleaved Diffusion Models for Exemplar-based Image Translation

Junyoung Seo*, Gyuseong Lee*, Seokju Cho, Jiyoung Lee, Seungryong Kim
AAAI Conference on Artificial Intelligence (AAAI), 2023.
[Project] [Link]

ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization

Jiwon Kim*, Yeongjo Min*, Daehwan Kim*, Kwangrok Ryoo, Gyuseong Lee, Junyoung Seo, and Seungryong Kim
European Conference on Computer Vision (ECCV), 2022.
[Link]

Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labels

Jiwon Kim*, Kwangrok Ryoo*, Junyoung Seo*, Gyuseong Lee* , Daehwan Kim, Hansang Cho, and Seungryong Kim
IEEE Conf. Computer Vision Pattern Recognition (CVPR), 2022
[Link]

Academic Services

Reviewer

• Computer Vision and Pattern Recognition (CVPR), 2023, 2024
• European Conference on Computer Vision (ECCV), 2024
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

Honors

• Award for Academic Excellence
  • 1st Semester of 2021, 2st Semester of 2020, and 1st Semester of 2020
  • Korea University, Korea
• KEPCO Scholarship
  • Korea Electric Power Corporation, Korea (Mar. 2021)
• 3rd Prize, Barrier-free App Development Contest
  • Incorporated Association GreenLight and HYUNDAI AutoEver, Korea (Feb. 2021)
• Special Award in Self-driving RC Car Development. Korea Embedded Software Contest
  • HYUNDAI MOBIS, Korea (Jan. 2021)
• Professor’s Association(Seokrimhoe) Scholarship
  • Korea University, Korea (Sep. 2020)
• Grand Prize in App Development, SK Smarteen App Challenge
  • SK, Korea (Dec. 2013)

Projects

• Automation of Deep Learning Model Update Using Unlabeled Data
  • Samsung Electro-Mechanics (2021-2022)

Skills

• Deep Learning, Machine Learning
  • Pytorch, Numpy
• Programming Languages
  • Python, JavaScript, C/C++
• Framework and Tool
  • Flutter, MATLAB