3D Cuboid Annotation
Spatial labels delivered to a versioned coordinate and geometry specification.
3D Point Cloud & LiDAR Annotation Services for Autonomous Systems
3D cuboids, point segmentation, multi-sweep tracking and camera-LiDAR fusion delivered with calibration validation and component-level geometric QA.
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What Is 3D Point Cloud & LiDAR Annotation?
Annotation gives sparse sensor geometry meaning through objects, surfaces, drivable regions and tracks. A 3D cuboid records x, y and z position, physical dimensions and heading.
Image Annotation and Video Annotation cover 2D-only work.
3D Annotation Types We Deliver
Point-Level Semantic Segmentation
Spatial labels delivered to a versioned coordinate and geometry specification.
3D Instance Segmentation
Spatial labels delivered to a versioned coordinate and geometry specification.
Multi-Sweep Object Tracking
Spatial labels delivered to a versioned coordinate and geometry specification.
Camera-LiDAR Sensor Fusion
Spatial labels delivered to a versioned coordinate and geometry specification.
Radar and Multi-Sensor Fusion
Spatial labels delivered to a versioned coordinate and geometry specification.
3D Lane and Road Marking
Spatial labels delivered to a versioned coordinate and geometry specification.
Drivable and Free Space
Spatial labels delivered to a versioned coordinate and geometry specification.
Ground and Surface Classification
Spatial labels delivered to a versioned coordinate and geometry specification.
3D Keypoints and Pose
Spatial labels delivered to a versioned coordinate and geometry specification.
Occupancy Grid Labeling
Spatial labels delivered to a versioned coordinate and geometry specification.
Aerial and Survey Point Clouds
Spatial labels delivered to a versioned coordinate and geometry specification.
Fusion Is a Calibration Problem Before Annotation Begins
We validate extrinsics, temporal synchronisation, ego-motion compensation, intrinsic distortion and long-capture drift before production. Projection agreement separates calibration error from annotation error.
Our 3D Annotation Process
- Sensor review and calibration validation
- Schema and guideline authoring
- Annotator qualification
- Pilot with geometric metrics
- Production annotation
- Multi-tier 3D and projection review
- Delivery and iteration
How We Measure 3D Annotation Quality
3D IoU, translation error, dimensions, heading, ID switches, fragmentation, fusion projection agreement, point inclusion, ground-plane consistency and distance-band reporting.
What the Sensor Can and Cannot Tell You
Minimum point thresholds, occlusion rules, weather artefacts, reflective surfaces, ground ambiguity, heading ambiguity and sensor-specific density are documented before scale. Unsupported geometry is flagged rather than invented.
Output Formats and Delivery
PCD, LAS, LAZ, PLY, KITTI BIN, ROS bag and E57 inputs; KITTI, nuScenes, Waymo-style, SUSTechPOINTS, JSON, point-wise labels, CSV cuboids and custom outputs with coordinate conventions confirmed in the pilot.
Where 3D Annotation Is Used
Autonomous vehicles, ADAS, warehouse robotics, drones, surveying, construction, mining, agriculture, smart cities and rail. Explore Robotics Training Data Services.
Model-Assisted Annotation, Security and Cost
Pre-generation is measured by distance-band recall and avoided where it biases rare, far-field or benchmark data. Secure projects use vetted access, audit trails and defined retention. Cost depends on label type, objects, density, tracking, fusion, thresholds and scene difficulty.
Related Services and Proof
AI Data Collection Data Cleaning & Validation AI Model Testing Computer vision samples Case studies
Frequently Asked Questions About 3D & LiDAR Annotation
What is 3D point cloud annotation?
3D point cloud annotation labels LiDAR or depth-sensor data through oriented cuboids, point classes, surfaces and persistent tracks.
What is the difference between a 3D cuboid and a 2D bounding box?
A 3D cuboid adds physical position, dimensions and yaw to the image-plane location represented by a 2D box.
Why does calibration matter for 3D annotation?
Incorrect extrinsic calibration makes correct geometry project incorrectly into a camera view. Calibration must be validated before production.
How do you measure 3D annotation quality?
We report 3D IoU plus translation, dimension and heading error separately, track consistency, fusion agreement and accuracy by distance band.
What formats do you support?
Inputs include PCD, LAS or LAZ, PLY, KITTI BIN, ROS bag and E57; outputs include KITTI, nuScenes, Waymo-style, SUSTechPOINTS and custom schemas.
How do we start?
Share 20 to 50 difficult frames, calibration files and your schema for a measured pilot.