38 citations · 92 across the 16 of their papers we have counts for
20 papers
RadarGSOcc: Doppler-Aware 3D Semantic Occupancy Prediction Using 4D Radar Tensor with Geometric-Semantic Feature Extraction
Christofel Rio Goenawan, Dong-Hee Paek, Seung-Hyun Kong
3D semantic occupancy prediction is crucial for autonomous driving, but camera-based methods degrade in low-light conditions and LiDAR-based methods are sensitive to adverse weathe…
STAR: Scene- and Task-Aware 4D Radar Preprocessing Towards End-to-End Cognitive Radar
Seung-Hyun Song, Dong-Hee Paek, Seung-Hyun Kong
Four-dimensional (4D) Radar has emerged as a key sensor for environmental perception, providing range, azimuth, elevation, and Doppler measurements while remaining robust to illumi…
IMM-based Multiple Object Tracking using a State Prediction Neural Network
Chan-Bin Lim, Dong-Hee Paek, Seung-Hyun Kong
Object tracking is essential for autonomous vehicles to avoid obstacles and plan routes. Radar maintains detection performance even in adverse weather and can measure relative velo…
Frequency Estimation Based on SNR-adaptive Frequency Estimator Under Wide SNR Range
Hee-Yang Jung, Dong-Hee Paek, Woo-Jin Jung +1
Frequency estimation is the problem of estimating individual tone frequencies from noisy multi-tone sinusoidal signals. Existing frequency estimation methods have difficulty accura…
Stereo 4D Radar for 3D Object Detection: Integrating Geometric Alignment and Absolute Velocity Estimation
Seung-Hyun Song, Dong-Hee Paek, Woong-Chan Byun +1
Four-dimensional (4D) Radar is a powerful sensing modality capable of detecting surrounding three-dimensional (3D) objects under diverse weather conditions and providing Doppler-ba…
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…
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…
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…
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…
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…
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…
SpikingRTNH: Spiking Neural Network for 4D Radar Object Detection
Dong-Hee Paek, Seung-Hyun Kong
Recently, 4D Radar has emerged as a crucial sensor for 3D object detection in autonomous vehicles, offering both stable perception in adverse weather and high-density point clouds…
Open-Source Autonomous Driving Software Platforms: Comparison of Autoware and Apollo
Hee-Yang Jung, Dong-Hee Paek, Seung-Hyun Kong
Full-stack autonomous driving system spans diverse technological domains-including perception, planning, and control-that each require in-depth research. Moreover, validating such…
Efficient 4D Radar Data Auto-labeling Method using LiDAR-based Object Detection Network
Min-Hyeok Sun, Dong-Hee Paek, Seung-Hyun Song +1
Focusing on the strength of 4D (4-Dimensional) radar, research about robust 3D object detection networks in adverse weather conditions has gained attention. To train such networks,…
RTNH+: Enhanced 4D Radar Object Detection Network using Combined CFAR-based Two-level Preprocessing and Vertical Encoding
Seung-Hyun Kong, Dong-Hee Paek, Sangjae Cho
Four-dimensional (4D) Radar is a useful sensor for 3D object detection and the relative radial speed estimation of surrounding objects under various weather conditions. However, si…
Enhanced K-Radar: Optimal Density Reduction to Improve Detection Performance and Accessibility of 4D Radar Tensor-based Object Detection
Dong-Hee Paek, Seung-Hyun Kong, Kevin Tirta Wijaya
Recent works have shown the superior robustness of four-dimensional (4D) Radar-based three-dimensional (3D) object detection in adverse weather conditions. However, processing 4D R…
Row-wise LiDAR Lane Detection Network with Lane Correlation Refinement
Dong-Hee Paek, Kevin Tirta Wijaya, Seung-Hyun Kong
Lane detection is one of the most important functions for autonomous driving. In recent years, deep learning-based lane detection networks with RGB camera images have shown promisi…
K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions
Dong-Hee Paek, Seung-Hyun Kong, Kevin Tirta Wijaya
Unlike RGB cameras that use visible light bands (384769 THz) and Lidars that use infrared bands (361331 THz), Radars use relatively longer wavelength radio bands (77$\s…
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling
Kevin Tirta Wijaya, Dong-Hee Paek, Seung-Hyun Kong
Existing point cloud feature learning networks often incorporate sequences of sampling, neighborhood grouping, neighborhood-wise feature learning, and feature aggregation to learn…
K-Lane: Lidar Lane Dataset and Benchmark for Urban Roads and Highways
Donghee Paek, Seung-Hyun Kong, Kevin Tirta Wijaya
Lane detection is a critical function for autonomous driving. With the recent development of deep learning and the publication of camera lane datasets and benchmarks, camera lane d…