Joonkyu Park | Computer Vision Research
JK Joonkyu Park
Portrait of Joonkyu Park

PERSONAL RESEARCH PROFILE

Joonkyu Park

Computer Vision Researcher

Seoul National University · CV Lab Seoul, Republic of Korea

CURRICULUM VITAE Download CV PDF Document ↓

01

Personal Information

I am a computer vision researcher at Seoul National University, working under the supervision of Prof. Kyoung Mu Lee. My research focuses on generative image restoration, 3D vision, and human-centric visual intelligence.

Research Interests

  • Image Restoration & Diffusion Models
  • 3D Vision & Gaussian Splatting
  • Human-Object Interaction

02

Selected Publications

Preview image for Learning to Corrupt for Better Restoration

ECCV, 2026.

Learning to Corrupt for Better Restoration

Joonkyu Park, Wooseok Lee, Jaeha Kim, Sehoon Kim, Bokyeung Lee, and Kyoung Mu Lee

Preview image for Bridging the Distribution Gap to Harness Pretrained Diffusion Priors for Super-Resolution

ICLR, 2026.

Bridging the Distribution Gap to Harness Pretrained Diffusion Priors for Super-Resolution

Joonkyu Park, and Kyoung Mu Lee

Preview image for Mars2 2025 challenge on multimodal reasoning

ICCVW, 2025.

Mars2 2025 challenge on multimodal reasoning

Peng Xu, Shengwu Xiong, Jiajun Zhang, Yaxiong Chen, Bowen Zhou, Chen Change Loy, ..., Joonkyu Park (121 additional authors)

Preview image for A 3D Scene-Based Dataset for Realistic Image Deblurring

NeurIPS, 2024.

A 3D Scene-Based Dataset for Realistic Image Deblurring

Dongwoo Lee, Joonkyu Park, and Kyoung Mu Lee

Preview image for 3D Hand Sequence Recovery from Real Blurry Images and Event Stream

ECCV, 2024.

3D Hand Sequence Recovery from Real Blurry Images and Event Stream

Joonkyu Park, Gyeongsik Moon, Weipeng Xu, Evan Kaseman, Takaaki Shiratori, and Kyoung Mu Lee

Preview image for Rethinking RGB Color Representation for Image Restoration Models

ArXiv, 2024.

Rethinking RGB Color Representation for Image Restoration Models

Jaerin Lee, Joonkyu Park, Sungyong Baik, Kyoung Mu Lee

Preview image for Adaptive Context and Latent Information Blending for Face Image Inpainting

SPL, 2023.

Adaptive Context and Latent Information Blending for Face Image Inpainting

Joonkyu Park, Cheeun Hong, Sungyong Baik, and Kyoung Mu Lee

Preview image for Extract-and-Adaptation Network for 3d Interacting Hand Mesh Recovery

ICCVW (Oral), 2023.

Extract-and-Adaptation Network for 3d Interacting Hand Mesh Recovery

Joonkyu Park*, Daniel Sungho Jung*, Gyeongsik Moon*, and Kyoung Mu Lee.

Preview image for Content-Aware Local Gan for Photo-Realistic Super-Resolution

ICCV, 2023.

Content-Aware Local Gan for Photo-Realistic Super-Resolution

Joonkyu Park, Sanghyun Son, and Kyoung Mu Lee.

Preview image for Recovering 3d Hand Mesh Sequence from a Single Blurry Image. A new dataset and temporal unfolding

CVPR, 2023.

Recovering 3d Hand Mesh Sequence from a Single Blurry Image. A new dataset and temporal unfolding

Yeonguk Oh*, Joonkyu Park*, Jaeha Kim*, Gyeongsik Moon, and Kyoung Mu Lee.

Preview image for Pay Attention to Hidden States for Video Deblurring, Ping-pong Recurrent Neural Networks and Selective Non-Local Attention

arXiv 2022.

Pay Attention to Hidden States for Video Deblurring, Ping-pong Recurrent Neural Networks and Selective Non-Local Attention

Joonkyu Park, Seungjun Nah, and Kyoung Mu Lee.

Preview image for Occlusion-Robust 3d Hand Mesh Estimation Network

CVPR, 2022.

Occlusion-Robust 3d Hand Mesh Estimation Network

Joonkyu Park, Yeonguk Oh, Gyeongsik Moon, Hongsuk Choi, and Kyoung Mu Lee

Preview image for Learning to Estimate Robust 3d Human Mesh from in-the-wild Crowded Scenes

CVPR, 2022.

Learning to Estimate Robust 3d Human Mesh from in-the-wild Crowded Scenes

Hongsuk Choi, Gyeongsik Moon, Joonkyu Park, and Kyoung Mu Lee.

Preview image for Recurrence-in-Recurrence Networks for Video Deblurring

BMVC, 2021.

Recurrence-in-Recurrence Networks for Video Deblurring

Joonkyu Park, Seungjun Nah, and Kyoung Mu Lee.

Publication Pages

03

Selected Projects

Preview image for DM-SR

DM-SR

Single-Step Real-World Super-Resolution