A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Autonomous vehicles (AV) are rapidly becoming integrated into everyday life, with several
countries anticipating their inclusion in public transport networks in the coming years. Safety …

Autonomous driving requires an accurate and fast 3D perception system that includes 3D
object detection, tracking, and segmentation. Although recent low-cost camera-based …

Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …

Anatomical consistency in biomarker segmentation is crucial for many medical image
analysis tasks. A promising paradigm for achieving anatomically consistent segmentation …

With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …

Robust and accurate geometric understanding against adverse weather conditions is one
top prioritized conditions to achieve a high-level autonomy of self-driving cars. However …

Camera and radar sensors have significant advantages in cost, reliability, and maintenance
compared to LiDAR. Existing fusion methods often fuse the outputs of single modalities at …

We present a method for inferring dense depth from a camera image and a sparse noisy
radar point cloud. We first describe the mechanics behind mmWave radar point cloud …

Millimeter-wave (mmWave) radar, with its high resolution, sensitivity to micro-vibrations, and
adaptability to various environmental conditions, holds immense potential across multi …