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About myself
About myself
I'm a PhD student in the Department of Electrical Engineering at Korea Advanced Institute of Science & Technology (KAIST), working under the guidance of Prof. Munchurl Kim at VICLab.
My research focuses on deep learning-based computer vision, such as self-supervised monocular depth estimation, 3D reconstruction, and generative models.
Email: jaeho.moon@kaist.ac.kr
[CV][Google Scholar][LinkedIn]
Education
Education
03.2023 - Present Ph.D. in Electrical Engineering, KAIST
Advisor: Prof. Munchurl Kim
03.2021 - 02.2023 M.S. in Electrical Engineering, KAIST
Advisor: Prof. Munchurl Kim
03.2016 - 02.2021 B.S. in School of Computing, KAIST
08.2019 - 02.2020 Exchange student at Technische Universität Darmstadt, Germany
06.2019 - 07.2019 Exchange student at the University of California, Santa Cruz, United States
Preprints
Preprints
Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation
Jaeho moon*, Jeonghwan Yun*, Jaehyun Kim*, Jaehyup Lee, Munchurl Kim
arXiv preprint, 2024
[project page ] [arxiv]
SplineGS: Robust Motion-Adaptive Spline for Real-Time Dynamic 3D Gaussians from Monocular Video
Jongmin Park*, Minh-Quan Viet Buit*, Juan Luis Gonzalez Bello, Jaeho moon, Jihyung Oh, Munchurl Kim
CVPR, 2025
[project page ] [arxiv]
ABBSPO: Adaptive Bounding Box Scaling and Symmetric Prior based Orientation Prediction for Detection Aerial Image Objects
Woojin Lee*, Hyugjae Chang*, Jaeho Moon , Jaehyup Lee , Munchurl Kim
CVPR, 2025
[project page ]
Publications
Publications
From-Ground-To-Objects: Coarse-to-Fine Self-supervised Monocular Depth Estimation of Dynamic Objects with Ground Contact Prior
Jaeho moon, Juan Luis Gonzalez Bello, Byeongjun Kwon, Munchurl Kim
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
[project page ] [paper] [arxiv]
Detail-Preserving Self-Supervised Monocular Depth with Self-Supervised
Structural Sharpening
Juan Luis Gonzalez Bello, Jaeho moon, Munchurl Kim
LatinX in AI Workshop at IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
[paper]
Research Project Experience
Research Project Experience
04.2022 - Present SW STAR LAB (IITP)
Deep Learning-based Rendering of Spatial Video with Stationary and Dynamic Scenes
08.2023 - Present Integrated Satellite-based Applications Development for Korea Coast Guard
Deep-learning-based Illegal Ship and Contaminant Detection in Ocean SAR Imagery
03.2021 - 02.2022 Microsoft Research Asia
Deep Video Depth Estimation
Work Experience
Work Experience
03.2020 - 02.2021 AI Engineer, Classum
Developed a search engine utilizing sparse retrieval (BM25) and contextual embedding models such as BERT and RoBERTa.
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