9 datasets found

The dataset used in the paper is a large-scale point cloud compression framework, which can organize sparse and un-structured point clouds in a memory-efficient way.

The 3DLoMatch [12] is a registration dataset with low overlap pairs between 10% − 30%.

The dataset used for testing the compact geometric features on laser scan data.

The dataset used for testing the compact geometric features.

The dataset used for learning compact geometric features for local geometry in unstructured point clouds.

The KITTI odometry dataset is a collection of 22 sequences, containing point clouds, images, and GPS recordings of inner-city traffic, residential areas, highway scenes, and...

The PREDATOR dataset used for point cloud registration

The dataset used for the MVP Point Cloud Registration Challenge 2021

Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...