IEEE

PVC-SSD: Point-Voxel Dual-Channel Fusion With Cascade Point Estimation for Anchor-Free Single-Stage 3-D Object Detection

Abstract: Existing single-stage 3-D object detection algorithms, whether relying on point or voxel methodologies, face challenges in achieving high-performance detection across diverse object ...
IEEE

Mask-SL RCNN: Feature-Enhanced 3D Object Detection Network for Point Clouds

Abstract: At present, with the original point cloud as input, most of the object detectors use Pointnet++ to extract features of the point cloud based on the Farthest Point Sampling (FPS). However, ...
TechAnnouncer

Mastering Code: The Absolute Best Books to Learn Programming Languages

We’ve put together a list of some of the best books to learn programming languages, covering everything from writing clean ...
IEEE

Reliability-Oriented Asymmetric Power Device Size Selection of Neutral-Point Clamped Inverter Considering Mission Profiles

Abstract: One of the major drawbacks of the neutral-point clamped (NPC) inverter is unequal power loss distribution among power devices, which leads to unequal thermal loadings. Therefore, certain ...
IEEE

TM2B: Transformer-Based Motion-to-Box Network for 3D Single Object Tracking on Point Clouds

Abstract: 3D single object tracking plays a crucial role in numerous applications such as autonomous driving. Recent trackers based on motion-centric paradigm perform well as they exploit motion cues ...
IEEE

VeloVox: A Low-Cost and Accurate 4D Object Detector with Single-Frame Point Cloud of Livox LiDAR

Abstract: Combining motion prediction in LiDAR-based 3D object detection is an effective method for improving overall accuracy, especially the downstream autonomous driving tasks. The recent ...
IEEE

Dense Sequential Fusion: Point Cloud Enhancement Using Foreground Mask Guidance for Multimodal 3-D Object Detection

Abstract: Object detection forms the foundation of safe autonomous vehicle (AV) operation. LiDAR and camera are both widely used detection devices, yet they each come with their unique advantages and ...
IEEE

Frustum PointVoxel-RCNN: A High-Performance Framework for Accurate 3D Object Detection in Point Clouds and Images

Abstract: Precise 3D object detection plays a pivotal role within the perception module of autonomous vehicles. Many approaches have shown promising results for 3D object detection with lidar.
IEEE

3-D Object Detection With Balanced Prediction Based on Contrastive Point Loss

Abstract: Object detection on point clouds is widely used in autonomous driving technology. Recent studies have demonstrated that good feature representation is the key to 3-D object detection, ...
IEEE

2D Instance-Guided Pseudo-LiDAR Point Cloud for Monocular 3D Object Detection

Abstract: Monocular three-dimensional (3D) scene understanding tasks, e.g., object size angle and 3D position, estimation are challenging to perform. More successful current methods usually require ...
IEEE

Infrastructure-Side Point Cloud Object Detection via Multi-Frame Aggregation and Multi-Scale Fusion

Abstract: In recent years, with the advancement of artificial intelligence technology, autonomous driving technologies have gradually emerged. 3D object detection using point clouds has become a key ...