Search Results for "multi"

LAStools is a collection of efficient, multi-core, scriptable tools for processing LiDAR data. It supports various formats, including LAS, LAZ, Terrasolid BIN, and ESRI Shapefiles, providing a comprehensive suite for LiDAR data management and analysis.

RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar Graph-Based SLAM approach based on an incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determine how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to...

Multi-sensor labeling platform for robotics and autonomous vehicles. The platform for fast and accurate multi-sensor data annotation. Label in-house or with an external workforce. Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more. Our labeling interfaces are set up to label fast and precise.

GLTF/GLB Windows Shell Extension: This shell extension automatically adds thumbnail images to .glb files in Windows File Explorer and provides a right click menu option to generate a 3D preview image for .gltf files. Supports multi-file select and directory processing. Pre-built Windows x64 installer available at https://buymeacoffee.com/nathancrews/e/255640 LAS/LAZ Pointcloud Windows Shell Extension: This "quick viewer" shell extension provides a Windows File Explorer right click menu option to quickly generate 3D preview images for large and small .las and .laz files. ...

3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. ...