Detection, segmentation, tracking and 3D scene data.
Overview
What is computer vision?
Computer vision models need large volumes of precisely annotated visual data. Every pixel counts, from autonomous vehicles to retail analytics.
Vision AI has no tolerance for annotation errors. A mislabeled pedestrian or a loose bounding box can cascade into dangerous failures in production.
Precise object localization for detection and autonomous systems.
Semantic and instance segmentation for scene understanding.
Pose estimation and anatomical landmark annotation.
3D point cloud annotation with multi-sensor alignment.
Workflow
How we do it
- 01Taxonomy definition
Define annotation classes, hierarchies and edge case rules for your model.
- 02Tool setup
Configure tooling for your task: CVAT, Label Studio or our platform.
- 03Annotation sprint
Specialists annotate boxes, polygons, keypoints, semantic maps or 3D cuboids.
- 04Cross-review QA
Peer review with IoU scoring to hold spatial accuracy thresholds.
- 05Dataset export
Export in COCO JSON, YOLO, Pascal VOC or custom format with train, val and test splits.
Case study
Train a computer vision model on real-world driving scenarios
Custom 3D bounding box pipeline with sensor fusion validation across 50+ object classes.
Ready to get startedwith computer vision?
Tell us about your project and we will scope a pilot within 48 hours.