Jae Young Lee
Orcid: 0000-0002-7450-5023Affiliations:
- LG Innotek, Ansan, Gyeonggi-do, Korea
- Korea Advanced Institute of Science and Technology, KAIST, School of Electrical Engineering, Daejeon, Korea
- Sogang University, Department of Electronic Engineering, Seoul, Korea (former)
According to our database1,
Jae Young Lee
authored at least 19 papers
between 2016 and 2025.
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Bibliography
2025
Proceedings of the 22nd International Conference on Ubiquitous Robots, 2025
2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Proceedings of the Shape in Medical Imaging - International Workshop, 2024
Stereo-Matching Knowledge Distilled Monocular Depth Estimation Filtered by Multiple Disparity Consistency.
Proceedings of the IEEE International Conference on Acoustics, 2024
Modeling Stereo-Confidence out of the End-to-End Stereo-Matching Network via Disparity Plane Sweep.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Multi-scale foreground-background separation for light field depth estimation with deep convolutional networks.
Pattern Recognit. Lett., 2023
I See-Through You: A Framework for Removing Foreground Occlusion in Both Sparse and Dense Light Field Images.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023
Proceedings of the IEEE International Conference on Robotics and Automation, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the 34th British Machine Vision Conference 2023, 2023
2022
CoRR, 2022
Proceedings of the Uncertainty in Artificial Intelligence, 2022
2021
Complex-Valued Disparity: Unified Depth Model of Depth from Stereo, Depth from Focus, and Depth from Defocus Based on the Light Field Gradient.
IEEE Trans. Pattern Anal. Mach. Intell., 2021
Occlusion Handling by Successively Excluding Foregrounds for Light Field Depth Estimation Based on Foreground-Background Separation.
IEEE Access, 2021
2018
Reduction of Aliasing Artifacts by Sign Function Approximation in Light Field Depth Estimation Based on Foreground-Background Separation.
IEEE Signal Process. Lett., 2018
2017
Depth Estimation From Light Field by Accumulating Binary Maps Based on Foreground-Background Separation.
IEEE J. Sel. Top. Signal Process., 2017
Global motion compensated saliency estimation with a hand-held camera for video retiming.
Proceedings of the IEEE International Conference on Consumer Electronics, 2017
2016
Reconstruction of an all-in-focus image by region-adaptive fusion of limited depth-of-field images.
Proceedings of the IEEE International Conference on Consumer Electronics, 2016