18 datasets found

The dataset used in the paper is a LiDAR point cloud dataset, which is a sparse 3D point cloud acquired by LiDAR sensors.

A dataset of vehicular wireless channel measurements, including LiDAR and Radar data.

A LiDAR simulator for autonomous driving that generates annotated point cloud data.

A method for LiDAR 3D point-cloud semantic segmentation exploiting perceptual information from RGB images and spatial-depth information from point clouds.

A real-world dataset for LiDAR-based end-to-end navigation, consisting of 32km of driving data with 29km for training and 3km for testing.

The proposed method applies selective stereo matching (SSM) followed by binary anisotropic diffusion tensor (B-ADT) aided smoothing.

Learning compact representations for LiDAR completion and generation.

The Argoverse 2 motion forecasting dataset contains 250,000 driving scenarios, each 11 seconds long. These scenarios cover 6 geographical regions and represent 763 total hours...

GEDI is a full-waveform LiDAR sensor onboard the International Space Station (ISS) that has been in operation between latitudes of 51.6° N and 51.6° S since 2019.

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

The KITTI360 dataset is used for evaluating the proposed Tuple-Circle loss function for cross-modality feature learning. The dataset consists of image and LiDAR scan pairs.

A LiDAR-based 3D object detection dataset.

A LiDAR-based 3D object detection dataset.

A multi-modal dataset capturing self-driving scenes in various conditions, including different times of day and weather.

The dataset used in the paper is the KITTI depth completion dataset, which supplies collection of sparse LiDAR scans and corresponding semi-dense depth maps as ground truth.

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...