LiDAR Segmentation
LiDAR Segmentation for ADAS with 97%+ Quality
Challenge
Our client needed a highly skilled and rapidly scalable annotation team capable of segmenting and labeling massive LiDAR datasets with exceptional precision to ensure safe and reliable ADAS performance. They required a workforce that could maintain strict accuracy standards to prevent safety-critical misinterpretations, scale quickly to manage large and complex data volumes, and undergo specialized training to deliver consistent, high-quality annotations across all projects.
DDD’s Solution
DDD met these requirements by rapidly expanding its LiDAR segmentation team from 20 to over 500 trained annotators within just a few months, fully onboarded to the client’s platform. Led by experienced team leads and trainers, we have consistently labeled more than 10,000K scenes annually for over two years. Through our robust annotator-reviewer workflow, we’ve maintained over 97% per-object quality (F1/IOU), ensuring precision, consistency, and reliability at scale.
Providing consistent, high-precision data labeling for safe, reliable ADAS applications.
Impact
By rapidly expanding and training a specialized workforce, we have provided consistent, high-quality data labeling for over two years, powering model accuracy, reliability for product verification, and safety case. This ongoing collaboration showcases DDD’s capability to manage large, complex annotation pipelines while meeting stringent performance and quality benchmarks.