Comprehensive review of deep learning-based 3d point cloud completion processing and analysis
Point cloud completion is a generation and estimation issue derived from the partial point
clouds, which plays a vital role in the applications of 3D computer vision. The progress of …
clouds, which plays a vital role in the applications of 3D computer vision. The progress of …
Hyperbolic chamfer distance for point cloud completion
Chamfer distance (CD) is a standard metric to measure the shape dissimilarity between
point clouds in point cloud completion, as well as a loss function for (deep) learning …
point clouds in point cloud completion, as well as a loss function for (deep) learning …
InfoCD: a contrastive chamfer distance loss for point cloud completion
A point cloud is a discrete set of data points sampled from a 3D geometric surface. Chamfer
distance (CD) is a popular metric and training loss to measure the distances between point …
distance (CD) is a popular metric and training loss to measure the distances between point …
Point Cloud Completion: A Survey
Point cloud completion is the task of producing a complete 3D shape given an input of a
partial point cloud. It has become a vital process in 3D computer graphics, vision and …
partial point cloud. It has become a vital process in 3D computer graphics, vision and …
[HTML][HTML] Deep-learning-based point cloud completion methods: A review
K Zhang, A Zhang, X Wang, W Li - Graphical Models, 2024 - Elsevier
Point cloud completion aims to utilize algorithms to repair missing parts in 3D data for high-
quality point clouds. This technology is crucial for applications such as autonomous driving …
quality point clouds. This technology is crucial for applications such as autonomous driving …
Enhancing extraction of two-dimensional engineering drawings from three-dimensional data of existing buildings
N Li, Y Wang, W Geng, Z Li - Journal of Building Engineering, 2023 - Elsevier
Accurately extracting two-dimensional (2D) engineering drawings from existing buildings'
three-dimensional (3D) data is crucial for building renovation, protection, and research. This …
three-dimensional (3D) data is crucial for building renovation, protection, and research. This …
TopologyFormer: structure transformer assisted topology reconstruction for point cloud completion
Point cloud completion is a fundamental task to enhance the completeness and authenticity
of point cloud data captured in the real world. Existing mainstream methods tend to obtain …
of point cloud data captured in the real world. Existing mainstream methods tend to obtain …
Hyperbolic Chamfer Distance for Point Cloud Completion and Beyond
Chamfer Distance (CD) is widely used as a metric to quantify difference between two point
clouds. In point cloud completion, Chamfer Distance (CD) is typically used as a loss function …
clouds. In point cloud completion, Chamfer Distance (CD) is typically used as a loss function …
Imagine with the Teacher: Complete Shape in a Multi-View Distillation Way
Z Luo, L Wang, G Qian, L Lu - arxiv preprint arxiv:2501.19270, 2025 - arxiv.org
Point cloud completion aims to recover the completed 3D shape of an object from its partial
observation caused by occlusion, sensor's limitation, noise, etc. When some key semantic …
observation caused by occlusion, sensor's limitation, noise, etc. When some key semantic …
Research on aircraft skin rivet detection technology based on the normal vector-density clustering algorithm
L Huang, X Huang - Review of Scientific Instruments, 2024 - pubs.aip.org
Riveting quality is crucial to an aircraft's overall aerodynamic performance and fatigue life. In
order to effectively extract the point cloud of rivet heads and analyze the quality of riveting …
order to effectively extract the point cloud of rivet heads and analyze the quality of riveting …