Sanghun Jung
I am a second-year PhD student at the University of Washington, where I am advised by Byron Boots. I am interested in visual learning for robotics, bridging the gap between visual perception and robot planning/control.
My recent research covers effective transfer learning for LiDAR segmentation and traversability prediction from visual cues by self-supervision.
Mail: shjung13 [at] cs [dot] washington [dot] edu
CV  / 
LinkedIn  / 
Google Scholar  / 
Github
|
|
|
DARPA Robotic Autonomy in Complex Environments with Resiliency (RACER)
University of Washington, 2023
|
|
Demonstrating Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics
Tyler Han, Preet Shah, Sidharth Rajagopal, Yanda Bao, Sanghun Jung, Sidharth Talia, Gabriel Guo, Bryan Xu, Bhaumik Mehta, Emma Romig, Rosario Scalise, Byron Boots
Under Review, 2025  
arXiv
|
|
Details Matter for Indoor Open-vocabulary 3D Instance Segmentation
Sanghun Jung, Jingjing Zheng, Ke Zhang, Nan Qiao, Albert Y. C. Chen, Lu Xia, Chi Liu, Yuyin Sun, Xiao Zeng, Hsiang-Wei Huang, Byron Boots, Min Sun, and Cheng-Hao Kuo
Under Review, 2025  
|
|
Aim My Robot: Precision Local Navigation to Any Object
Xiangyun Meng, Xuning Yang, Sanghun Jung, Fabio Ramos, Srid Sadhan Jujjavarapu, Sanjoy Paul, and Dieter Fox
RA-L, 2025  
arXiv
|
|
V-STRONG: Visual Self-Supervised Traversability Learning for Off-road Navigation
Sanghun Jung, JoonHo Lee, Xiangyun Meng, Byron Boots, and Alexander Lambert
ICRA, 2024  
arXiv
|
|
LiDAR-UDA: Self-ensembling Through Time for Unsupervised LiDAR Domain Adaptation
Amirreza Shaban*, JoonHo Lee*, Sanghun Jung*, Xiangyun Meng, and Byron Boots
ICCV, 2023   Oral Presentation (<1.8%)
arXiv
/
code
|
|
CAFA: Class-aware Feature Alignment for Test-time Adaptation
Sanghun Jung, Jungsoo Lee, Nanhee Kim, Amirreza Shaban, Byron Boots, and Jaegul Choo
ICCV, 2023  
arXiv
|
|
DebiasBench: Benchmark for Fair Comparison of Debiasing in Image Classification
Jungsoo Lee, Juyoung Lee, Sanghun Jung, and Jaegul Choo
Preprint, 2023  
arXiv
|
|
CG-NeRF: Conditional Generative Neural Radiance Fields
Kyungmin Jo*, Gyumin Shim*, Sanghun Jung, Soyoung Yang, and Jaegul Choo
WACV, 2023  
arXiv
|
|
3D-GIF: 3D-Controllable Object Generation via Implicit Factorized Representations with Unposed 2D Images
Minsoo Lee, Chaeyeon Chung, Hojun Cho, Minjung Kim, Sanghun Jung, Minhyuk Sung, and Jaegul Choo
Preprint, 2022  
arXiv
|
|
Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation
Sanghun Jung*, Jungsoo Lee*, Daehoon Gwak, Sungha Choi, and Jaegul Choo
ICCV, 2021   Oral Presentation (<3.0%)
arXiv
/
code
|
|
RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening
Sungha Choi*, Sanghun Jung*, Huiwon Yun, Joanne Taery Kim, and Jaegul Choo
CVPR, 2021   Oral Presentation (<4.1%)
arXiv
/
code
|
|
Visualizing for the Non-Visual: Enabling the Visually Impaired
to Use Visualization
Jinho Choi, Sanghun Jung, Deokgun Park, Jaegul Choo, and Niklas Elmqvist
EuroVIS, 2019
|
|