Junho Kim | 김준호

I am a Research Intern at RideFlux, where I work on autonomous driving. I received my B.S. in Electrical Engineering from Kookmin University, where I worked with Prof. Seongwon Lee on 3D/4D scene understanding. Previously, I was a Research Intern at CARIAD, advised by Dr. Xavier Timoneda.

I am applying to PhD programs for Fall 2027.

Email  /  Google Scholar  /  Github  /  CV

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Research

My long-term goal is to develop world models that enable autonomous agents to understand the physical world, predict the consequences of their actions, and make reliable decisions.

I am particularly interested in representations for action and multi-agent counterfactual world modeling, decision-relevant representations and predicting how the world and other agents may respond to different actions.

Building on my work in 3D/4D scene understanding and autonomous driving, I aim to bridge perception, world modeling, and decision-making.

* Equal contribution. † Corresponding author.
FreeView project image FreeView: Robust 3D Reconstruction from Uncurated Views
Consensus-based visual-geometric distractor rejection for robust 3D reconstruction
Junho Kim*, Hyunyoung Choi*, Seongwon Lee†
Submitted to ICRA'27
arXiv

Feed-Forward Refinement Selective Appearance Refinement for Feed-Forward 3D Gaussian Splatting
A plug-and-play module that selectively corrects low-confidence appearance predictions.
Junho Kim, Jiseok Kim, Seongwon Lee†
International Conference on Control, Automation, and Systems (ICCAS), 2026
arXiv

RayOcc project image RayOcc: Occlusion-Aware Ray Occupancy Estimation via Gaussian Mixture Intensity
Multi-surface Ray occupancy modeling with Gaussian mixture model.
Junho Kim, Seongwon Lee†
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026
project page / arXiv

VG3T: Visual Geometry Grounded Gaussian Transformer
Cross-view geometry grounding produces cleaner 3D occupancy with fewer Gaussians.
Junho Kim, Seongwon Lee†
IEEE International Conference on Robotics and Automation (ICRA), 2026
project page / arXiv / code

Project
High-Fidelity Vehicle Representation High-Fidelity Vehicle Representation via 3D Gaussian Splatting
Reflective vehicle reconstruction with disentangled diffuse and specular appearance.
Junho Kim, Sangho Byeon, Jiseok Kim, Seongwon Lee
Team Lead of We-Meet Project (Fall 2025)

Bosch Future Mobility Challenge 2024 Bosch Future Mobility Challenge 2024
Real-time autonomous driving perception and deployment on an embedded platform.
Minchan Jeong, Junho Kim, Dahyeon Ko, Jaehyoung Park, Donghwan Seo
Perception Engineer / ROS, Multi-View 3D object detection, V2X
3rd Prize, (top 3 out of 80 teams worldwide)

Experience
RideFlux, Seoul, South Korea
2026.08 - Present

Perception Research Intern
Advisor: Dr. Hawook Jeong
Kookmin University, Seoul, South Korea
2019.03 - 2026.08

B.S. in Electrical Engineering
Advisor: Prof. Seongwon Lee
CARIAD SE, Ingolstadt, Germany
2024.07 - 2024.12

Sensor Fusion Research Intern
Advisor: Dr. Xavier Timoneda
SEA:ME, Wolfsburg, Germany
2023.07 - 2024.06

Out-Bound Program
Advisor: Prof. Jongchan Kim
Republic of Korea Army, Gyeonggi-Do, South Korea
2020.12 - 2022.6

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Last updated: Aug. 6, 2026