Labeler & Reviewer – Robotic Video Annotation Project
Labeled and reviewed everyday activity videos to support robotic model training for AI systems. Ensured high accuracy and consistency by upholding quality standards and correcting inconsistencies. Provided structured feedback for improvement to other annotators. • Labeled approximately 4 hours of video per week for model training. • Validated annotations for quality and protocol adherence. • Enhanced annotation accuracy and consistency. • Supported scalable, production-ready datasets for robotics.