Autonomous vehicles
Full-stack perception datasets: detection, tracking, and drivable space.
Advanced & 3D Labeling
3D Point Cloud Annotation Services
Cuboids, segmentation, and multi-sensor fusion labeling for LiDAR and 3D perception systems.
Overview
3D perception data is unforgiving: sparse points, moving sensors, and centimeter-level tolerances. Vidyut Data's 3D teams annotate LiDAR sweeps and fused camera-LiDAR scenes — cuboids, point-level segmentation, and tracking across sweeps — using calibrated tooling and physics-sanity QA (no floating cars, no clipping pedestrians).
What's included
- ✓3D cuboids with heading, dimensions, and attributes
- ✓Point-level semantic and instance segmentation
- ✓Object tracking across sequential sweeps
- ✓2D-3D linking for camera-LiDAR sensor fusion
- ✓HD map feature annotation (lanes, signs, curbs)
- ✓Occlusion-aware interpolation with human keyframe review
Use cases
Robotics & AMRs
Indoor 3D scene labeling for navigation and manipulation.
HD mapping
Lane-level map features from mobile mapping fleets.
Infrastructure inspection
Asset detection in aerial and terrestrial scans.
How we work
1
Scope & pilot
We review your data, define the labeling guide together, and run a paid pilot batch so you can judge quality before scaling.
2
Team & calibrate
A dedicated, trained team ramps on your guidelines, benchmarked against gold-standard tasks until accuracy targets are hit.
3
Produce & QA
Production batches flow through multi-tier QA — consensus review, statistical sampling, and edge-case escalation.
4
Deliver & iterate
Data ships in your format with accuracy reports. Guidelines evolve with your model's failure cases.
Frequently asked questions
How do you guarantee quality for3d point cloud annotation services?
Every project runs through multi-tier QA: annotators are benchmarked against gold-standard tasks before production, batches are statistically sampled against agreed accuracy targets, and ambiguous cases are escalated and documented in a living labeling guide. You receive accuracy reports with every delivery.
Can we start with a small pilot before committing?
Yes — we recommend it. A paid pilot batch on your real data lets you evaluate our quality, turnaround, and communication before scaling. Pilot learnings become the project's labeling guide.
How is our data kept secure?
Client data is encrypted in transit and at rest, access is limited to the assigned project team under NDAs, and we support VPN-restricted or client-hosted workflows where data cannot leave your environment. Retention and certified deletion terms are set per engagement.
What tools and output formats do you support?
We work in your annotation platform or ours, and deliver in the format your pipeline expects — COCO, YOLO, Pascal VOC, JSON, CSV, or a custom schema — with delivery via API, cloud bucket, or scheduled export.
Ready to scale your3d point cloud annotation services?
Start with a pilot batch — see our quality on your data before you commit.