27 datasets found

Learning from bounding-boxes annotations has shown great potential in weakly-supervised 3D point cloud instance segmentation. However, we observed that existing methods would...

The dataset is a collection of 3D point clouds of daily terrains, including level ground, up stairs, and down stairs.

The SemanticKITTI dataset is a LiDAR-based semantic segmentation dataset, which consists of 10 sequences for training and 1 for validation.

A saliency map is constructed for 3D point-clouds to measure the contribution (importance) of each point in a point cloud to model prediction loss.

The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.

The dataset used in the paper is the KITTI dataset, which is a benchmark for monocular depth estimation. The dataset consists of a large collection of images and corresponding...

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...