Jae-Yeul Kim

According to our database, Jae-Yeul Kim authored at least 16 papers between 2020 and 2025.

Collaborative distances:

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

2025

A Training-Free Style-Personalization via Scale-wise Autoregressive Model.

Kyoungmin Lee, Jihun Park, Jongmin Gim, Wonhyeok Choi, Kyumin Hwang, Jaeyeul Kim, Sunghoon Im

CoRR, July, 2025

Bridging Geometric and Semantic Foundation Models for Generalized Monocular Depth Estimation.

Sanggyun Ma, Wonjoon Choi, Jihun Park, Jaeyeul Kim, Seunghun Lee, Jiwan Seo, Sunghoon Im

CoRR, May, 2025

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

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

IEEE Robotics Autom. Lett., April, 2025

A Training-Free Style-aligned Image Generation with Scale-wise Autoregressive Model.

Jihun Park, Jongmin Gim, Kyoungmin Lee, Minseok Oh, Minwoo Choi, Jaeyeul Kim, Woo Chool Park, Sunghoon Im

CoRR, April, 2025

2024

Density-aware Domain Generalization for LiDAR Semantic Segmentation.

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

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 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