Research
I'm interested in computer vision for 3D scene understanding, such as (1) 3D Visual Language Model, (2) 3D Scene Reconstruction and Neural Rendering and (3) 3D Vehicle/Object Perception. Some papers are highlighted .
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3D Visual Language Model (TBU)
Junha Lee*, Chunghyun Park*, Jaesung Choe , Jonathan Tremblay, De-An Huang, Yu-Chiang Frank Wang, Jan Kautz, Minsu Cho, Christopher Choy
*Equal contribution
TBU
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3D Gaussian Splatting (TBU)
Cheng Sun, Jaesung Choe , Yu-Chiang Frank Wang
TBU
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Spacetime Surface Regularization for Neural Dynamic Scene Reconstruction
Jaesung Choe , Christopher Choy, Jaesik Park, In So Kweon, Anima Anandkumar
ICCV 2023
Paper
Propose spacetime surface regularization for 4D surface reconstruction.
PointMixer: MLP-Mixer for Point Cloud Understanding
Jaesung Choe* , Chunghyun Park*, Francois Rameau, Jaesik Park, In So Kweon
*Equal contribution
ECCV 2022
Paper / Code / Poster / Video
Design a new MLP-only architecture for 3D points.
Facial Depth and Normal Estimation using Single Dual-Pixel Camera
Minjun Kang, Jaesung Choe , Hyowon Ha, Hae-Gon Jeon, Sunghoon Im, In So Kweon, Kuk-Jin Yoon
ECCV 2022
Paper / Code
Face Reconstruction from Monocular Dual-Pixel Camera.
VolumeFusion: Deep Depth Fusion for 3D Scene Reconstruction
Jaesung Choe , Sunghoon Im, Francois Rameau, Minjun Kang, In So Kweon
ICCV 2021
Paper / Video / Slide
Deep learning based Depth Fusion algorithm for Indoor Scene Reconstruction.
Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation
Jaesung Choe , Kyungdon Joo, Tooba Imtiaz, In So Kweon
RA-L 2021
Paper (RA-L) / Paper (ICRA) / Video
Depth estimation using LiDAR pointcloud and stereo images.
Talks
DGIST colloquium, April 2024
Kakao Brain, May 2022