6 citations · 9 across the 6 of their papers we have counts for
6 papers · 1 filter
Bridging Spectral-wise and Multi-spectral Depth Estimation via Geometry-guided Contrastive Learning
Ukcheol Shin, Kyunghyun Lee, Jean Oh
Deploying depth estimation networks in the real world requires high-level robustness against various adverse conditions to ensure safe and reliable autonomy. For this purpose, many…
Learning to Control Camera Exposure via Reinforcement Learning
Kyunghyun Lee, Ukcheol Shin, Byeong-Uk Lee
Adjusting camera exposure in arbitrary lighting conditions is the first step to ensure the functionality of computer vision applications. Poorly adjusted camera exposure often lead…
Complementary Random Masking for RGB-Thermal Semantic Segmentation
Ukcheol Shin, Kyunghyun Lee, In So Kweon +1
RGB-thermal semantic segmentation is one potential solution to achieve reliable semantic scene understanding in adverse weather and lighting conditions. However, the previous studi…
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning
Ukcheol Shin, Kyunghyun Lee, In So Kweon
In this paper, we propose a multi-objective camera ISP framework that utilizes Deep Reinforcement Learning (DRL) and camera ISP toolbox that consist of network-based and convention…
Depth Completion using Plane-Residual Representation
Byeong-Uk Lee, Kyunghyun Lee, In So Kweon
The basic framework of depth completion is to predict a pixel-wise dense depth map using very sparse input data. In this paper, we try to solve this problem in a more effective way…
Self-Supervised Depth and Ego-Motion Estimation for Monocular Thermal Video Using Multi-Spectral Consistency Loss
Ukcheol Shin, Kyunghyun Lee, Seokju Lee +1
A thermal camera can robustly capture thermal radiation images under harsh light conditions such as night scenes, tunnels, and disaster scenarios. However, despite this advantage,…