SuP: Sub-cloud Driven Point Cloud Registration
SuP turns low-overlap point cloud registration into high-overlap sub-cloud anchor mining, using DSAM, OPS, MPN, and merge-to-match to recover reliable correspondences from ambiguous partial scans.
Jan 1, 2026
Dynamic correlation network and structure-aware matching for robust point cloud registration
Relative rotations between point clouds pose significant challenges for reliable correspondence estimation.
Jan 1, 2026
An Improved Graph Attention Network for Semantic Segmentation of Industrial Point Clouds in Automotive Battery Sealing Nail Defect Detection
Accurate defect detection in automotive battery sealing nails is vital for safety and reliability.
Jan 1, 2026
SemReg: Semantics-Constrained Point Cloud Registration
SemReg incorporates semantic labels as geometric registration constraints, enabling robust point cloud alignment even in textureless or symmetry-ambiguous regions where purely geometric methods fail, with state-of-the-art results on indoor and outdoor benchmarks.
Sep 1, 2024
TopFormer: Topology-Aware Transformer for Point Cloud Registration
TopFormer augments transformer-based point cloud registration with topological structure descriptors, improving correspondence quality in geometrically repetitive and low-texture regions by encoding how local surface neighbourhoods connect globally.
Apr 1, 2024
Gap measurement method based on projection lines and convex analysis of 3D point clouds
A geometric method combining projection-line fitting and convex analysis on 3D point clouds precisely measures gap dimensions in assembled components, providing a robust alternative to contact gauging for automated industrial inspection.
Jan 1, 2024
A Point Cloud Contour Extraction Method based on Plane Segmentation
A method based on plane segmentation and dimensionality reduction for extracting incomplete and slow contour features of object point clouds is proposed.
Jan 1, 2024
Weighted Point Cloud Normal Estimation
A weighted normal estimation scheme adaptively weights neighbouring points based on local surface geometry confidence, producing more accurate normals at sharp features and noisy regions than standard PCA-based and learning-based methods.
Jul 1, 2023
Towards uniform point distribution in feature-preserving point cloud filtering
A point cloud filtering method simultaneously preserves sharp geometric features and promotes spatially uniform point distribution, resolving the typical trade-off where feature-preserving filters cluster points near sharp edges.
Jan 1, 2023
Random screening-based feature aggregation for point cloud denoising
Random screening selects informative subsets of neighbouring points for feature aggregation during point cloud denoising, reducing sensitivity to outliers and improving denoised geometry quality over fixed-neighbourhood aggregation schemes.
Jan 1, 2023