31 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 point cloud processing pipeline that transforms the point cloud into a compact, regular grid and performs neural operations on the grid.

Real-time point cloud processing is fundamental for lots of computer vision tasks, while still challenged by the computational problem on resource-limited edge devices.

The dataset used in the paper is a 3D point cloud classification task, where the authors use the ModelNet40, ModelNet10, and ShapeNetPart datasets.

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

The LASDU dataset is a large-scale ALS dataset acquired from a highly-dense urban area.

The ISPRS benchmark dataset is an ALS benchmark dataset obtained in August 2008 using a Leica ALS50 system with an average flying height of 500m and a 45◦ field of view.

Geometric distortion metrics for point cloud compression.

The dataset is used to estimate the parameters of a Markov-Modulated Jump-Diffusion Model (MMJDM) for stock prices.

The KITTI-360 dataset is an extension of the KITTI dataset, containing 10 new sequences recorded in 2013, with a focus on 360-degree views.

The dataset used in the paper is KITTI-360 and KITTI odometry datasets.

Lidar panoptic segmentation for autonomous driving

Nuscenes is a large-scale autonomous driving dataset that provides high-resolution BEV semantic occupancy labels for roads and vehicles.

The KITTI odometry dataset is a benchmark for evaluating visual odometry and other computer vision tasks. It contains a large collection of images and corresponding ground-truth...

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 dataset used in the paper for 6Dof object pose estimation using RGB-D images.

A Full Flow Bidirectional Fusion Network for 6D Pose Estimation from a single RGBD image