Chung Min Kim

I am a second-year PhD student in at UC Berkeley, where I am advised by Ken Goldberg and Angjoo Kanazawa. I received my dual B.S. degree in EECS (Electrical Engineering and Computer Science) and Mechanical Engineering from UC Berkeley in 2021. I am currently funded by the NSF GRFP. 🐻

My research interests include computer vision and robotics. I'm interested in connecting large vision-language models with 3D representations (e.g., NeRFs). My goal is to apply these models to robots in the real world, which is challenging due to lack of structure and large variability in the real world. 🦾

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⚙️ Under construction ⚙️

GARField: Group Anything with Radiance Fields
Chung Min Kim*, Mingxuan Wu*, Justin Ker*, Ken Goldberg, Matthew Tancik, Angjoo Kanazawa
*Equal contribution
arXiv 2023
arXiv / Website

Hierarchical grouping in 3D by training a scale-conditioned affinity field from multi-level masks
LERF-TOGO: Language Embedded Radiance Fields for Zero-Shot Task-Oriented Grasping
Adam Rashid*, Satvik Sharma*, Chung Min Kim, Justin Kerr, Lawrence Yunliang Chen, Angjoo Kanazawa, Ken Goldberg
*Equal contribution
CoRL 2023 Oral, Best Paper Finalist
arXiv / Website

LERF's multi-scale semantics enables 0-shot language-conditioned part grasping for a wide variety of objects.
LERF: Language Embedded Radiance Fields
Justin Kerr*, Chung Min Kim*, Ken Goldberg, Angjoo Kanazawa, Matthew Tancik
*Equal contribution ICCV 2023 Oral
arXiv / Website

Grounding CLIP vectors volumetrically inside a NeRF allows flexible natural language queries in 3D
Mechanical Search on Shelves with Efficient Stacking and Destacking of Objects
Letian Fu*, Huang Huang*, Michael Danielczuk, Chung Min Kim, Zachary Tam, Jeffrey Ichnowski, Anelia Angelova, Brian Ichter, and Ken Goldberg, *Equal contribution
ISRR 2022 - arXiv / Website

Mechanical Search on Shelves using a Novel “Bluction” Tool
Huang Huang, Michael Danielczuk, Chung Min Kim, Letian Fu, Zachary Tam, Jeffrey Ichnowski, Anelia Angelova, Brain Ichter, Ken Goldberg,
ICRA 2022 - IEEE / arXiv

IPC-GraspSim: Reducing the Sim2Real Gap for Parallel-Jaw Grasping with the Incremental Potential Contact Model
Chung Min Kim, Michael Danielczuk, Isabella Huang, Ken Goldberg
ICRA 2022 - IEEE / arXiv / Video / Code / Website

IPC-GraspSim is a novel grasp simulator that extends Incremental Potential Contact (IPC) to model both the dynamics and the deformation of compliant jaw tips during robot grasping.

Source code for this page was taken from Jon Barron's website.