How We Annotated 10,000 LiDAR Frames in Just $899
A leading autonomous vehicle startup needed high-quality 3D LiDAR annotations—but had a limited budget. They turned to GetAnnotator and achieved over 10,000 frames annotated for just $1000, maintaining both quality and speed.
Client Profile
- Industry: Autonomous Vehicles / Robotics
- Size: Early-stage startup (Series A)
- Need: Annotate LiDAR point cloud frames (bounding boxes + segmentation)
- Deadline: 4 weeks
- Budget: <$1,000
The Challenge
- LiDAR Annotation is labor-intensive and typically expensive
- Most vendors charge $0.10–$0.50 per frame
- Client wanted custom classes, consistent annotation rules, and QA process
- Needed a team that could scale fast, stay affordable, and be quality-driven
Our Solution – GetAnnotator
Plan Chosen: Skilled Plan – $499/month (hired 2 annotators)
- Dedicated annotator (2+ years experience)
- 1 Project Manager included
- Slack + Google Sheet-based tracking
Custom Setup:
- Defined 6 object classes (vehicles, pedestrians, bikes, traffic cones, barriers, trees)
- Frame-by-frame annotation with bounding boxes and 3D segmentation
- Used client’s own web annotation tool, integrated via API
- QA every 1000 frames using a hybrid review: human + automation
Automation Boost:
- Used pre-labeling with open-source models to reduce raw time
- Built a simple Python script to batch QA for missing/inaccurate tags
- Uploaded auto-QA reports to Google Sheets daily
Results
| Metric | Outcome |
|---|---|
| Total Frames | 10,000 |
| Turnaround | 18 days |
| Accuracy | 96.3% QA pass |
| Total Cost | $998 |
| Cost/Frame | $0.099 |
NOTE: Saved ~80% compared to the average market rate.
What Made It Work
- Affordable workforce (India)
- Micro-team structure: 1 annotator, 1 QA, 1 PM
- Transparent workflow tracking is shared with the client daily
Frequently Asked Questions
Q1. How did GetAnnotator manage to annotate 10,000 LiDAR frames for just $899?
Through optimized workflows, remote expert teams, and smart use of automation, we cut costs drastically without compromising quality.
Q2. Does the low cost affect the accuracy of LiDAR annotations?
Not at all. Every frame went through multi-step QA with human-in-the-loop validation to ensure precision in 3D labeling.
Q3. What types of LiDAR annotations can GetAnnotator handle?
We specialize in 3D bounding boxes, segmentation, object tracking, and sensor fusion tasks across autonomous driving and robotics.
Q4. How do you scale LiDAR annotation while keeping costs predictable?
By combining automation-assisted labeling with a distributed remote workforce, we handle high-volume datasets at transparent, fixed costs.
Q5. Can my autonomous driving or robotics project achieve similar cost savings?
Yes. Whether you need 10,000 frames or millions, we can scale efficiently while keeping budgets under control.
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