Semi-Automated Data Annotation for Autonomous Vehicles
Published:Dec 31, 2025 14:43
•1 min read
•ArXiv
Analysis
This paper addresses the critical challenge of efficiently annotating large, multimodal datasets for autonomous vehicle research. The semi-automated approach, combining AI with human expertise, is a practical solution to reduce annotation costs and time. The focus on domain adaptation and data anonymization is also important for real-world applicability and ethical considerations.
Key Takeaways
- •Proposes a semi-automated data annotation pipeline for multisensor datasets.
- •Combines AI with human expertise to reduce annotation costs and time.
- •Employs 3D object detection for initial annotations.
- •Includes data anonymization and domain adaptation techniques.
- •Supports the development of large annotated datasets for autonomous vehicle research.
Reference
“The system automatically generates initial annotations, enables iterative model retraining, and incorporates data anonymization and domain adaptation techniques.”