Autonomous Vehicles
End-to-end perception datasets covering object detection, multi-frame tracking, and free-space mapping.
Advanced & 3D Labeling
3D Point Cloud Annotation Services
Cuboid labeling, segmentation, and sensor-fusion annotation for LiDAR-based perception systems.
Overview
3D perception data leaves little room for error — sparse point returns, sensor drift, and object boundaries that must hold up to centimeter-level scrutiny. Vidyut Data's 3D annotation teams work directly with LiDAR point clouds and fused camera-LiDAR scenes, handling cuboid placement, point-level segmentation, and cross-sweep object tracking. Every output passes through calibrated annotation tooling and a physical-plausibility QA pass — checking that objects sit where they should, don't float above the ground plane, and don't bleed into neighboring pedestrians or structures.
What's included
- ✓3D cuboid annotation with orientation, dimensions, and object attributes
- ✓Point-level segmentation, both semantic (class) and instance (individual object)
- ✓Multi-sweep object tracking to maintain identity across frames
- ✓Camera-to-LiDAR correspondence for sensor fusion pipelines
- ✓HD map feature labeling — lane boundaries, signage, curb lines
- ✓Keyframe-based interpolation with manual review for occluded objects
Use cases
Robotics & Autonomous Mobile Robots
Indoor 3D environment labeling to support navigation, obstacle avoidance, and manipulation tasks.
HD Mapping
Precision lane-level map feature extraction from mobile mapping vehicle data.
Infrastructure Inspection
Object and asset identification from aerial and ground-based 3D scan data.
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 your 3d point cloud annotation services?
Start with a pilot batch — see our quality on your data before you commit.