Jae-Yeul Kim

According to our database, Jae-Yeul Kim authored at least 12 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Flow4D: Leveraging 4D Voxel Network for LiDAR Scene Flow Estimation.

Jaeyeul Kim, Jungwan Woo, Ukcheol Shin, Jean Oh, Sunghoon Im

CoRR, 2024

Rethinking LiDAR Domain Generalization: Single Source as Multiple Density Domains.

Jaeyeul Kim, Jungwan Woo, Jeonghoon Kim, Sunghoon Im

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Domain Generalization in LiDAR Semantic Segmentation Leveraged by Density Discriminative Feature Embedding.

Jaeyeul Kim, Jungwan Woo, Jeonghoon Kim, Sunghoon Im

CoRR, 2023

MSF-NET: Foreground Objects Detection With Fusion of Motion and Semantic Features.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2023

Automatic Extrinsic Calibration of a Camera and a 2D LiDAR With Point-Line Correspondences.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2023

2022

RVMOS: Range-View Moving Object Segmentation Leveraged by Semantic and Motion Features.

Jae-Yeul Kim, Jungwan Woo, Sunghoon Im

IEEE Robotics Autom. Lett., 2022

Foreground Object Detection in Visual Surveillance With Spatio-Temporal Fusion Network.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2022

Weakly Supervised Foreground Object Detection Network Using Background Model Image.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2022

2021

Spatio-Temporal Data Augmentation for Visual Surveillance.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2021

Generation of Background Model Image Using Foreground Model.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2021

2020

Extrinsic Calibration of a Camera and a 2D LiDAR Using a Dummy Camera With IR Cut Filter Removed.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2020

Foreground Objects Detection Using a Fully Convolutional Network With a Background Model Image and Multiple Original Images.

Jae-Yeul Kim, Jong-Eun Ha

IEEE Access, 2020