9 datasets found

TUM-MLS-2016: An annotated mobile lidar dataset of the TUM City Campus for semantic point cloud interpretation in urban areas.

Developing and testing robust autonomy: The university of sydney campus data set.

The Waymo dataset is a LiDAR-based semantic segmentation dataset, which consists of 798 sequences for training and 202 for validation.

The SynthCity dataset is used to generate synthetic LiDAR point cloud data.

The GTA-V dataset is used to generate synthetic LiDAR point cloud data.

The KITTI Object Detection Benchmark consists of 7,481 training images and 7,518 testing images, with 3D LiDAR point clouds and camera images.

The dataset used in the paper is a synthetic LiDAR point cloud dataset generated using the CARLA simulator.

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

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...