31 datasets found

LiDAR-based 3D object detection dataset

A benchmark for stereo matching and depth estimation.

LiDAR point-cloud segmentation is an important problem for many applications. For large-scale point cloud segmentation, the de facto method is to project a 3D point cloud to get...

The dataset used in the paper is a synthetic dataset for off-policy contextual bandits, with contexts x ∈ X, a finite set of actions A, and bounded real rewards r ∈ A → [0, 1].

A point cloud dataset with large quantity of dynamic instances, consisting of 2,988 real-world scans with point-level annotations.

The dataset used for 6D object pose estimation, consisting of images of 16 objects with varying levels of occlusion.

The dataset is a comprehensive review of over 100 transformer methods for different 3D vision tasks, including classification, segmentation, detection, completion, pose...

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.

Point cloud (PC) is a collection of points in 3D space, represented as P = {pk} = {(ck, rk)}, where ck = (xk, yk, zk) denotes the 3D coordinate of the k’th point, and rk is its...

3D object detection using point cloud (PC) data is essential for perception pipelines of autonomous driving, where efficient encoding is key to meeting stringent resource and...

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...