Hyunjoon Lee

I am an integrated MS/PhD student at VGI Lab (Visual and Geometric Intelligence Lab) at Seoul National University, where I am advised by Prof. Jaesik Park.

My research interests lie at the intersection of 3D vision and robotics. I am particularly interested in how we can leverage rich scene information to enhance robot manipulation capabilities in complex environments.

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Education

Seoul National University (SNU)

Seoul, Korea • Integrated M.S./Ph.D. in AI

Advisor: Jaesik Park
Mar. 2024 - Present
Sungkyunkwan University (SKKU)

Suwon, Korea • B.S. in Mechanical Engineering

Summa Cum Laude (1/131), GPA: 4.39/4.5
Mar. 2018 - Feb. 2024

Experience

Research Intern @ HuGe Lab, KAIST AI

Advisor: Beomjoon Kim

Developed a model to predict 6-DoF grasp poses using a depth sensor.
Jun. 2023 - Sep. 2023
Research Intern @ CSI Lab, SKKU

Advisor: Yusung Kim

Developed an RL agent using the PPO algorithm and transformer architecture.
Jan. 2023 - Jun. 2023
Research Intern @ CAMAS Lab, SKKU

Advisor: Jachoon Koo

Developed a mathematical model to elucidate the stiffness mechanism of the soft gripper.
Dec. 2019 - Mar. 2020

Research

HiDiGS: Training-free Hierarchical Clustering...

Hyunjoon Lee*, Eunsung Cha*, Jaesik Park

Under Review, 2026

We propose a training-free hierarchical clustering framework for open-vocabulary 3D Gaussian segmentation, unifying instance-level coherence and query flexibility via an efficient digraph-based formulation without per-scene optimization.

Feed-forward Multi-view 3D Reconstruction...

Jinmo Kim, Namtae Kim, Hyunjoon Lee, Seungha Kim, Jaesik Park

Under Review, 2026

We propose a feed-forward multi-view 3D reconstruction framework that explicitly reasons about occlusions by reconstructing missing latent tokens across views.

CF3: Compact and Fast 3D Feature Fields

Hyunjoon Lee, Joonkyu Min, Jaesik Park

ICCV (Main & Demonstrations Track), 2025

We propose a method to build compact and fast 3D Gaussian feature fields by effectively compressing and sparsifying Gaussians, achieving competitive performance with significantly fewer gaussians.

Project Page / arXiv / Code

Awards & Honors

Honorable Mention, Research Paper Competition, Seoul National University (Dec. 2025)
Outstanding Paper Presentation Award, Korea Computer Congress (Aug. 2025)
Invited Talk, SNU Graduate of AI Research Exchange (Jun. 2025)
Top Excellence Award, Creative Research Project, Seoul National University (Jun. 2025)
Outstanding Award, Demo Competition, Seoul National University (Jun. 2025)
Invited Talk, NaverLabs (Mar. 2025)
Dean's List Award, Sungkyunkwan University (May 2021, Oct 2020)
Scholarship for Academic Excellence, Sungkyunkwan University (Sep. 2018, Mar. 2019, Mar. 2020, Mar. 2021)

Patents

CF3: Compact and Fast 3D Feature Fields, KR Patent 10-2025-0093174