Person-MinkUNet: 3D Person Detection with LiDAR Point Cloud
In this preliminary work we attempt to apply submanifold sparse convolution to the task of 3D person detection. In particular, we present Person-MinkUNet, a single-stage 3D person detection network based on Minkowski Engine with U-Net architecture. The network achieves a 76.4% average precision (AP) on the JRDB 3D detection benchmark.
Code (1)
Tasks
Human DetectionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
2D vs. 3D LiDAR-based Person Detection on Mobile Robots
Person detection is a crucial task for mobile robots navigating in human-populated environments. LiDAR sensors are promising for this task, thanks to their accurate depth measurements and large field of view. Two types o…
Human DetectionGDPR-Compliant Person Recognition in Industrial Environments Using MEMS-LiDAR and Hybrid Data
The reliable detection of unauthorized individuals in safety-critical industrial indoor spaces is crucial to avoid plant shutdowns, property damage, and personal hazards. Conventional vision-based methods that use deep-l…
Point CloudsA Comparative Study of 3D Person Detection: Sensor Modalities and Robustness in Diverse Indoor and Outdoor Environments
Accurate 3D person detection is critical for safety in applications such as robotics, industrial monitoring, and surveillance. This work presents a systematic evaluation of 3D person detection using camera-only, LiDAR-on…
Autonomous DrivingPerson Detection and Tracking from an Overhead Crane LiDAR
This paper investigates person detection and tracking in an industrial indoor workspace using a LiDAR mounted on an overhead crane. The overhead viewpoint introduces a strong domain shift from common vehicle-centric LiDA…
The 2nd Place Solution from the 3D Semantic Segmentation Track in the 2024 Waymo Open Dataset Challenge
3D semantic segmentation is one of the most crucial tasks in driving perception. The ability of a learning-based model to accurately perceive dense 3D surroundings often ensures the safe operation of autonomous vehicles.…
3D Semantic SegmentationAutonomous VehiclesData AugmentationDiversity+3