Hyeonwoo Kim

"I like to research / propose novel ideas and hope to provide fresh experience to people." I’m researcher in computer vision, particularly in the field of 3D computer vision. I’ve worked as a software developer and AI applied researcher in past time and currently conducting research at SNU Visual Computing Lab with Prof. Hanbyul Joo.


Seoul National University
BS in Electric & Computer Engineering GPA: 3.76 / 4.3 Korea Science Academy of KAIST
High School GPA: 3.91 / 4.3
Seoul, Korea Mar 2017 - Aug 2023
Busan, Korea Mar 2014 - Feb 2017


Visual Computing Lab
Research Intern → MS/PhD Student
Seoul, Korea Mar 2023 - Current
Mainly researching on practical topics in 3D Computer Vision. Nowadays, interested in learning Human-Object Interaction (Affordance) which can be useful for perceiving environments and planning actions.
Applied AI Research Intern
Seongnam, Korea Jan 2023 - Mar 2023
Participate in WebtoonMe team in Generative Model Research. Study 2D Full Body Portrait Stylization (e.g. Real World → Webtoon Character) using diffusion model in dataset generation pipeline.
3D Vision Lab
Graduation Project Intern
Seoul, Korea Jul 2022 - Dec 2022
Participate in Graduation Project, Text Driven Stylization for Sparse Point Cloud. Study text based stylization task in point cloud while dealing with sparsity and noisiness of input point cloud.
Humanscape Inc.
Software Engineer
Seoul, Korea Apr 2020 - Jun 2022
Work as a Skilled Industrial Personnel for 23 months, doing alternative military service. Develop, launch, maintain Clinical Trials Korea web service. Design API and add features for Rarenote app and Rarenote Admin service.
SK Hynix
NAND Development, Analog IP Intern
Seongnam, Korea Jun 2019 - Aug 2019
Develop one-command script program to verify the exact feature matching of analog and digital circuit in various case of sequential input form.


2019 SK Hynix Scholarship
2017 Presedential Science Scholarship
2016 International Student Science Fair, Best Research & Development Award
2016 Samsung Humantech Paper Award, Gold Award


[arXiv 2024] Zero-Shot Learning for the Primitives of 3D Affordance in General Objects Hyeonwoo Kim*, Sookwan Han*, Patrick Kwon, Hanbyul Joo
[CVPR 2023, Highlight] Text2Scene: Text-driven Indoor Scene stylization with Part-aware Details Inwoo Hwang, Hyeonwoo Kim, Youngmin Kim
[Eurographics Short 2023] Text2PointCloud: Text-driven Stylization for Sparse PointCloud Inwoo Hwang, Hyeonwoo Kim, Donggeun Lim, Inbum Park, Youngmin Kim