user1802489

Completed 2,000+ hours of production labeling with primary focus on video and image labeling for AI model training. Performed frame-by-frame video annotation on first-person and task-based clips, labeling everyday and operational activities (e.g., pick/place, tool use, and household/industrial motions) with action segmentation and activity descriptions. Conducted image labeling including object classification/detection, attribute tagging, scene description, and multi-object annotation on still frames extracted from video and on standalone images. Reviewed sequences frame-by-frame to keep labels temporally aligned and avoid over/under-segmentation, and applied project taxonomies and edge-case rules (occlusion, partial objects, similar-looking items, unclear motion). Maintained high approval rates by following updated Atlas guidelines and supporting production targets while protecting quality through accurate labels first.

Completed 2,000+ hours of production labeling, primarily focused on video labeling and image labeling for AI model training. Performed video annotation on first-person and task-based clips, labeling everyday and operational activities (e.g., pick/place, tool use, household/industrial motions) according to Atlas guidelines. Conducted image labeling including object classification, attribute tagging, scene descriptions, and multi-object annotations on still frames extracted from video and standalone image tasks. Reviewed sequences frame-by-frame to keep labels aligned in time, reduce missed actions, and avoid over/under segmentation. Applied project taxonomies and edge-case rules (occlusion, partial objects, similar-looking items, unclear motion) to maintain label consistency and preserve high approval rates while meeting production targets.