Manufacturing
Factory Egocentric Tag Annotation
Egocentric video annotation for worker activity recognition and process optimization.
Person-level + Right-hand + Left-hand tagsExplore the case study
These case studies show how VIPRO Annotation handles difficult training data in practice. Factory Egocentric Tag Annotation covers worker activity tagged across more than one million first-person factory frames. FacePoint AI documents facial landmark annotation on 3D point-cloud scans. CityScope AI covers street scenes labelled with polygons and bounding boxes for urban perception. Each study explains the labelling rules, workflow and quality checks behind the delivered data, so you can judge how a similar project would run.
In short: Factory Egocentric Tag Annotation tagged worker activity across more than one million first-person factory frames. FacePoint AI annotated facial landmarks on about 500 3D point-cloud scans. CityScope AI labelled street scenes with polygons and bounding boxes to build an urban perception dataset for computer vision.
The collection Look closer.
Look closer.
Every label has a story.
From city surfaces to first-person factory work and facial landmark datasets—explore the annotation decisions, workflows, and quality checks behind each project.
03 / PROJECTS
3D Data
FacePoint AI — Facial Landmark Dataset
Turning captured facial geometry into a processed, annotated 3D dataset.
Point-cloud processing + Facial landmarksExplore the case study
Urban Perception
CityScope AI — Urban Perception Dataset
Turning complex urban environments into structured data for autonomous perception and 3D mapping.
Polygon + Bounding BoxExplore the case studyThe next chapterYour data.
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