3D cuboid labels on LiDAR point cloud for autonomous driving perception

LiDAR & 3D Point Cloud Annotation

Cuboids, segmentation, fusion, and lane geometry in 3D.

Cuboids, dense segmentation, sensor fusion, and lane/boundary lines—aligned to your autonomy or robotics stack.

Capabilities

Each capability pairs illustrative imagery with how we deliver it at production quality.

3D cuboid volumetric boxes on LiDAR point cloud for vehicles, pedestrians, and obstacles

3D Cuboid Labeling

Full 3D pose and dimensions on point clouds. Volumetric boxes for vehicles, pedestrians, and obstacles—multi-class L/W/H and orientation for planning beyond flat 2D.

Semantically segmented LiDAR point cloud with terrain, roads, and obstacles classified

Point Cloud Segmentation

Semantics on every point for full-scene context. Road, sidewalk, vegetation, vehicles, buildings—with strict QC so terrain vs. obstacles stays consistent in dense scenes.

Fused LiDAR and camera annotation with aligned 3D cuboids and semantic segments

Multi-Sensor Fusion

LiDAR + camera aligned in space and time. Cuboids and segments that agree in 3D and image space—cross-view checks (BEV, camera) for stronger detection and tracking.

3D polylines for lanes, road edges, and infrastructure on LiDAR point cloud

Lanes & Boundaries

3D polylines for lanes, curbs, and barriers. Centerlines, dividers, and road limits with elevation—topology-friendly for HD maps and lane-keeping.

Back to services