KITTI · Velodyne HDL-64E · frame 000010
3D cuboids
Oriented 3D boxes capture each object's position, size and heading in the point cloud, the core input for 3D detection.
3D point cloud data for AV and robotics
Accurately labeled LiDAR data that helps your autonomous systems see, sense and navigate the world with precision.
- Exports: KITTI · nuScenes · custom
- Cuboids · segmentation · polylines
- 98%+ accuracy guarantee
kitti_000010.binannotation
KITTI · Velodyne HDL-64E · frame 000010
public KITTI sample · dataset ground-truth labelsreal LiDAR
3D annotation types
Specialists in LiDAR and depth data
Our trained annotation specialists bring hands-on experience with LiDAR and depth-sensing data. From object detection to semantic segmentation, every 3D frame is labeled precisely to support complex AV and robotics workflows.
- vehicle
- pedestrian
- road
- ground
- vegetation
- structure
Semantic segmentation
Every point gets a class such as road, vehicle, pedestrian or vegetation, for dense scene understanding.
- KITTI · Velodyne HDL-64E · frame 000010
Polygon annotation
Polygons outline drivable areas, sidewalks and irregular objects that boxes can't describe.
Lane and polyline
Polylines trace lane markings, curbs and road edges for mapping and path planning.
2D boxes on camera frames
Synced camera images labeled alongside the point cloud for sensor-fusion models.
Real LiDAR data
One sweep, labeled three ways
A real Velodyne HDL-64E frame from the public KITTI dataset with its ground-truth labels: 3D cuboids, point-level classes and a bird's-eye view, plus a synced camera view.
- Object IDs persist across sweeps and cameras
- Attributes: occlusion, truncation, motion state
- Ego-motion compensated sequences
KITTI · Velodyne HDL-64E · frame 000010
Oriented boxes with size and heading, revealed as the sensor sweeps.
Use cases
Where teams put this data to work
Autonomous driving perception
3D detection and tracking of vehicles, pedestrians and cyclists for ADAS and self-driving stacks.
Robotics & AMRs
Obstacle and free-space labels so warehouse robots and mobile platforms navigate safely.
HD mapping
Lane lines, curbs, signs and poles traced in dense point clouds for map building.
Smart infrastructure
Roadside LiDAR labeled for traffic counting, near-miss detection and intersection safety.
How we work
From pilot to production
We start by understanding your sensors, classes and edge cases, then label and review point cloud data with expert teams, incorporating your feedback until every detail meets your standard.
- Step 01
Consult
We review your data, edge cases and success criteria, then write annotation guidelines with you.
- Step 02
Annotate
A trained team labels a pilot batch, following the agreed guidelines to the letter.
- Step 03
Calibrate
You review the pilot. We fold your feedback into the guidelines before scaling up.
- Step 04
Multi-layer QA
Every batch passes peer review, expert QA and automated checks before it leaves us.
- Step 05
Deliver
Labels ship in your format on your schedule, ready to drop into training.
Quality pipeline
Five checkpoints between raw data and your model
98%+
Accuracy guarantee
- 01AnnotatorLabels against your guidelines
- 02Peer reviewA second annotator reviews the work
- 03Expert QASenior reviewer samples and corrects
- 04Automated checksRules catch missing or invalid labels
- 05Client sign-offYou approve before final delivery
Results
Quality you can measure
- Accuracy guarantee
- 98%+Accuracy guarantee
- Returning clients
- 96%Returning clients
- Cost reduction
- 2.5xCost reduction
- Projects completed
- 200+Projects completed
“For our ADAS project, Intellisane AI delivered precise vehicle annotations across diverse traffic scenes, including multiple object classes and occlusion scenarios. Their expertise in automotive data workflows and quality-first mindset helped us pass all validation checks, with timely delivery and professional communication throughout.”
Raphael Lopez
Co-Founder & CTO, Felucca
Related
3D point cloud annotation supports robotics, automotive, logistics, mapping and more.
FAQ
Questions, answered
Something else on your mind? Email sales@intellisane.ai.
Get started
Let's scope your project
Tell us about your data. We'll come back with a plan and a free pilot batch so you can see the quality first.