[HTML][HTML] Point cloud registration for LiDAR and photogrammetric data: A critical synthesis and performance analysis on classic and deep learning algorithms
Abstract Three-dimensional (3D) point cloud registration is a fundamental step for many 3D
modeling and mapping applications. Existing approaches are highly disparate in the data …
modeling and mapping applications. Existing approaches are highly disparate in the data …
Cross-source point cloud registration: Challenges, progress and prospects
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 …
attention with the fast development background of 3D sensor technologies. Different from the …
Geometric transformer for fast and robust point cloud registration
We study the problem of extracting accurate correspondences for point cloud registration.
Recent keypoint-free methods bypass the detection of repeatable keypoints which is difficult …
Recent keypoint-free methods bypass the detection of repeatable keypoints which is difficult …
Regtr: End-to-end point cloud correspondences with transformers
Despite recent success in incorporating learning into point cloud registration, many works
focus on learning feature descriptors and continue to rely on nearest-neighbor feature …
focus on learning feature descriptors and continue to rely on nearest-neighbor feature …
Predator: Registration of 3d point clouds with low overlap
We introduce PREDATOR, a model for pairwise pointcloud registration with deep attention
to the overlap region. Different from previous work, our model is specifically designed to …
to the overlap region. Different from previous work, our model is specifically designed to …
Cofinet: Reliable coarse-to-fine correspondences for robust pointcloud registration
We study the problem of extracting correspondences between a pair of point clouds for
registration. For correspondence retrieval, existing works benefit from matching sparse …
registration. For correspondence retrieval, existing works benefit from matching sparse …
3D registration with maximal cliques
As a fundamental problem in computer vision, 3D point cloud registration (PCR) aims to
seek the optimal pose to align a point cloud pair. In this paper, we present a 3D registration …
seek the optimal pose to align a point cloud pair. In this paper, we present a 3D registration …
Pointdsc: Robust point cloud registration using deep spatial consistency
Removing outlier correspondences is one of the critical steps for successful feature-based
point cloud registration. Despite the increasing popularity of introducing deep learning …
point cloud registration. Despite the increasing popularity of introducing deep learning …
Rotation-invariant transformer for point cloud matching
The intrinsic rotation invariance lies at the core of matching point clouds with handcrafted
descriptors. However, it is widely despised by recent deep matchers that obtain the rotation …
descriptors. However, it is widely despised by recent deep matchers that obtain the rotation …
Spinnet: Learning a general surface descriptor for 3d point cloud registration
Extracting robust and general 3D local features is key to downstream tasks such as point
cloud registration and reconstruction. Existing learning-based local descriptors are either …
cloud registration and reconstruction. Existing learning-based local descriptors are either …