collaborators

8 papers

cs.CV2025

Availability-aware Sensor Fusion via Unified Canonical Space

Dong-Hee Paek, Seung-Hyun Kong

Sensor fusion of camera, LiDAR, and 4-dimensional (4D) Radar has brought a significant performance improvement in autonomous driving. However, there still exist fundamental challen…

cs.CV2025

Enhanced 3D Object Detection via Diverse Feature Representations of 4D Radar Tensor

Seung-Hyun Song, Dong-Hee Paek, Minh-Quan Dao +2

Recent advances in automotive four-dimensional (4D) Radar have enabled access to raw 4D Radar Tensor (4DRT), offering richer spatial and Doppler information than conventional point…

cs.CV2025

L2RDaS: Synthesizing 4D Radar Tensors for Model Generalization via Dataset Expansion

Woo-Jin Jung, Dong-Hee Paek, Seung-Hyun Kong

4-dimensional (4D) radar is increasingly adopted in autonomous driving for perception tasks, owing to its robustness under adverse weather conditions. To better utilize the spatial…

cs.CV2025

Efficient On-Chip Implementation of 4D Radar-Based 3D Object Detection on Hailo-8L

Woong-Chan Byun, Dong-Hee Paek, Seung-Hyun Song +1

4D radar has attracted attention in autonomous driving due to its ability to enable robust 3D object detection even under adverse weather conditions. To practically deploy such tec…

cs.CV2025

4DR P2T: 4D Radar Tensor Synthesis with Point Clouds

Woo-Jin Jung, Dong-Hee Paek, Seung-Hyun Kong

In four-dimensional (4D) Radar-based point cloud generation, clutter removal is commonly performed using the constant false alarm rate (CFAR) algorithm. However, CFAR may not fully…

cs.CV2025

Bayesian Approximation-Based Trajectory Prediction and Tracking with 4D Radar

Dong-In Kim, Dong-Hee Paek, Seung-Hyun Song +1

Accurate 3D multi-object tracking (MOT) is vital for autonomous vehicles, yet LiDAR and camera-based methods degrade in adverse weather. Meanwhile, Radar-based solutions remain rob…