The emerging topic of cross-source point cloud (CSPC) registration has attracted increasing
attention with the fast development background of 3D sensor technologies. Different from the …

Point cloud registration is a task to estimate the rigid transformation between two unaligned
scans, which plays an important role in many computer vision applications. Previous …

Point cloud registration is a crucial task in computer vision and 3D reconstruction, aiming to
align multiple point clouds to achieve globally consistent geometric structures. However …

Estimating rigid transformation using noisy correspondences is critical to feature-based point
cloud registration. Recently, a series of studies have attempted to combine traditional robust …

The expensive fine-grained annotation and data scarcity have become the primary
obstacles for the widespread adoption of deep learning-based Whole Slide Images (WSI) …

Self-supervised learning has achieved significant success in various fields such as point
cloud detection and segmentation. However, self-supervised learning for point cloud …

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 …

LiDAR and camera are two common vision sensors used in the real world, producing
complementary point cloud and image data. While multimodal data has previously been …

In this paper, we introduce a new outlier removal method that fully leverages geometric and
semantic information, to achieve robust registration. Current semantic-based registration …

针对道路场景下多智能网联汽车协同感知问题, 本文提出一种基于点云稀疏语义特征的智能网联
汽车协同感知配准算法. 所提算法旨在通过点云集成配准扩展智能网联汽车感知范围 …