Robotic Manipulation Video Annotation for Imitation Learning
Ongoing video-annotation program for robotic manipulation and imitation-learning datasets. Work includes frame-accurate object and gripper tracking, 3D cuboid annotation of manipulated objects, semantic segmentation of scenes and target objects, and key-point/pose labeling of robot end-effectors and human-demonstration hands across multi-view video. Built for training and evaluating manipulation and grasping policies. Quality is maintained through multi-pass human-in-the-loop QC, gold-standard benchmark tasks, consensus review, and per-batch acceptance thresholds.