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Read More3D LiDAR Annotation Services for Computer Vision
Digital Divide Data delivers accurate and scalable 3D LiDAR annotation services to train computer vision models with true depth, distance, and spatial awareness. Using expertly labeled 3D point cloud data, we help AI systems detect, recognize, and track objects reliably in complex real-world environments.
High-Precision 3D LiDAR Annotation for Real-World Spatial Intelligence
Digital Divide Data (DDD) is a global leader in 3D point cloud annotation and computer vision data services. We create high-quality labeled LiDAR datasets that accelerate AI adoption across autonomous systems, robotics, and geospatial intelligence, combining expert human annotation, production-grade quality frameworks, and secure infrastructure.
3D LiDAR Annotation Workflow End-to-End
Fully managed 3D LiDAR annotation, from raw point clouds to model-ready data
Use Case & Annotation Strategy Definition
Define object classes, annotation types, sensor configurations, and quality benchmarks.
Secure Data Ingestion & Preprocessing
LiDAR point cloud data is securely ingested, aligned, and prepared for annotation.
3D Point Cloud Annotation
Expert annotators label objects using cuboids, polylines, polygons, or segmentation techniques.
Multi-Layer Quality Assurance
Validation checks ensure spatial accuracy, consistency, and temporal alignment.
Edge Case & Bias Review
Rare scenarios and complex environments are reviewed to improve model robustness.
Delivery & Iteration
Datasets are delivered in required formats with continuous refinement as models evolve.
Our 3D LiDAR Annotation Solutions
Polyline Annotation
We annotate linear features such as road edges, lanes, curbs, and boundaries using precise polylines to support navigation and mapping applications.
Polygon Annotation
Complex objects and regions are outlined using accurate polygon shapes in 3D point clouds, enabling AI models to detect irregular boundaries with precision.
Semantic Segmentation Annotation
Every point or pixel in the LiDAR dataset is assigned a class label, allowing AI systems to understand full scenes and contextual relationships.
3D Bounding Box Annotation
We annotate objects in three dimensions with precise size, orientation, speed, yaw, and pitch, supporting accurate detection and tracking of vehicles, pedestrians, cyclists, and more.
3D LiDAR Use Cases
3D Object Detection & Tracking
Enable autonomous vehicles to accurately detect, classify, and track objects in three-dimensional space using annotated LiDAR point clouds.
Drivable Area, Lane & Road Boundary Detection
Train perception systems to identify drivable surfaces, lanes, curbs, and road edges with precise spatial awareness.
Obstacle Detection & Collision Avoidance
Support real-time safety systems by detecting static and dynamic obstacles in complex environments.
Robotic Navigation & Spatial Perception
Enable robots to navigate, localize, and interact with 3D environments using spatially accurate point cloud data.
Mapping & Localization for SLAM
Power simultaneous localization and mapping (SLAM) applications with high-quality annotated 3D sensor data.
Infrastructure Monitoring & Urban Planning
Analyze roads, bridges, buildings, and utilities using LiDAR annotation for planning and maintenance insights.
Agricultural Terrain & Asset Analysis
Support precision agriculture by analyzing terrain, crops, and equipment using 3D spatial data.
Geospatial & Defense Intelligence Workflows
Enable advanced situational awareness, mapping, and monitoring through annotated LiDAR and 3D datasets.
Industries We Support
Autonomous Driving
Training perception systems with accurate depth and spatial understanding for safe navigation.
Government
Supporting surveillance, infrastructure monitoring, and defense intelligence initiatives.
Geospatial Intelligence
Annotating LiDAR data for mapping, urban planning, and environmental monitoring.
Retail & E-Commerce
Supporting spatial analytics and automation in warehouses and fulfillment centers.
What Our Clients Say
Why Choose DDD?
Expert Human-in-the-Loop Annotation
Specialized LiDAR annotators ensure high spatial accuracy, consistency, and reliable handling of complex edge cases.
DDD’s Commitment to Security & Compliance
Your LiDAR and 3D point cloud data are protected at every stage through rigorous global standards and secure operational infrastructure.
SOC 2 Type 2
Verified controls across security, confidentiality, and system reliability
ISO 27001
Holistic information security management with continuous audits
GDPR & HIPAA Compliance
Responsible handling of personal and sensitive data
TISAX Alignment
Automotive-grade protection for mobility and vehicle-AI workflows
Read Our Latest Blogs
Explore expert perspectives on 3D point cloud annotation, LiDAR data training, and emerging trends.
3D Point Cloud Annotation for Autonomous Vehicles: Challenges and Breakthroughs
This blog will explore why 3D point cloud annotation is critical to autonomous driving, the challenges it presents, and...
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Multi-Sensor Data Fusion in Autonomous Vehicles — Challenges and Solutions
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Frequently Asked Questions
What is 3D LiDAR annotation?
3D LiDAR annotation involves labeling point cloud data generated by LiDAR sensors to help AI models understand depth, distance, object shape, and spatial relationships in real-world environments.
How does 3D point cloud annotation support computer vision models?
Annotated point cloud data acts as ground truth, enabling computer vision models to accurately detect, classify, and track objects in three-dimensional space.
What types of 3D LiDAR annotation does DDD provide?
DDD provides 3D bounding boxes (cuboids), polyline annotation, polygon annotation, and semantic segmentation for LiDAR and 3D point cloud datasets.
Can DDD scale large 3D LiDAR annotation projects?
Yes. DDD supports projects ranging from pilot datasets to large-scale LiDAR programs involving millions of point clouds.
How does DDD ensure accuracy in 3D LiDAR annotation?
We use specialized annotation tools, trained 3D annotators, spatial validation checks, and multi-layer quality assurance processes to ensure high accuracy and consistency.
How long does a 3D LiDAR annotation project take?
Timelines depend on dataset size, annotation complexity, and object classes, but our optimized workflows are designed to accelerate delivery.