IEEE

A Dual Attention KPConv Network Combined With Attention Gates for Semantic Segmentation of ALS Point Clouds

Abstract: Kernel point convolution (KPConv) defines convolutional weights based on Euclidean distances between kernel points and input points and has shown good segmentation results on several ...
IEEE

Multiprototype Relational Network for Few-Shot ALS Point Cloud Semantic Segmentation by Transferring Knowledge From Photogrammetric Point Clouds

Abstract: Existing airborne laser scanning (ALS) point cloud semantic segmentation approaches are limited by their overreliances on sufficient point-wise annotations that further confine their ...
IEEE

Robust Point Cloud Registration via Random Network Co-Ensemble

Abstract: Learning-based point cloud registration has achieved great success in recent years but is still limited by its generalization. The performance of these methods declines when they are ...
IEEE

MMCNet: Multi-Modal Point Cloud Completion Network Based on Self-Projected Views

Abstract: Obtaining defect-free point cloud data is challenging due to performance constraints of acquisition devices and unavoidable occlusion, making point cloud data completion critical. In recent ...
IEEE

Asynchronous Feedback Network for Perceptual Point Cloud Quality Assessment

Abstract: Recent years have witnessed the success of the deep learning-based technique in research of no-reference point cloud quality assessment (NR-PCQA). For a more accurate quality prediction, ...
IEEE

LSReg-Net: An End-to-End Registration Network for Large-Scale LiDAR Point Cloud in Autonomous Driving

Abstract: Large-scale point cloud registration is a fundamental problem for autonomous driving. To achieve alignment, most existing methods focus on local point cloud features for matching. However, ...
IEEE

SonarPoint: Weak-Heterogeneity Awareness Object Detection Network for 3D Sonar Point Cloud

Abstract: Underwater target detection is primarily achieved through two methods: optical imaging and underwater sonar. 3D sonar, as the most advanced underwater detection technology, is characterized ...
IEEE

HDMNet: A Hierarchical Matching Network with Double Attention for Large-scale Outdoor LiDAR Point Cloud Registration

Abstract: Outdoor LiDAR point clouds are typically large-scale and complexly distributed. To achieve efficient and accurate registration, emphasizing the similarity among local regions and ...
IEEE

BTPNet: A Probabilistic Spatial-Temporal Aware Network for Burn-Through Point Multistep Prediction in Sintering Process

Abstract: Burn-through point (BTP) is a very key factor in maintaining the normal operation of the sintering process, which guarantees the yield and quality of sinter ore. Due to the characteristics ...
IEEE

DNRHP: Temporal Network Representation Learning via Hawkes Point Process

Abstract: Graph neural networks (GNNs) have significantly advanced our ability to mine structured data, playing a central role in areas such as social networks and recommendation systems. However, ...
IEEE

DT-Net: Point Cloud Completion Network With Neighboring Adaptive Denoiser and Splitting-Based Upsampling Transformer

Abstract: Point cloud completion, which involves inferring missing regions of 3D objects from partial observations, remains a challenging problem in 3D vision and robotics. Existing learning-based ...
IEEE

AdverseNet: A LiDAR Point Cloud Denoising Network for Autonomous Driving in Rainy, Snowy, and Foggy Weather

Abstract: In the field of autonomous driving, a pressing issue is how to enable LiDAR to accurately perceive the 3-D environment around the vehicle without being affected by rain, snow, and fog.