Bounding Box Annotation Services for Accurate Object Detection Training Data

Bounding boxes are the foundation of many object detection models. They identify the position and scale of each object in an image or video frame. DataVLab provides bounding box annotation services that combine trained annotators, stable workforce continuity, and structured quality control to deliver consistent and accurate datasets.We support single object and multi object detection tasks, class hierarchies, occlusions, small object labeling, overlapping regions, and complex scenes with dense populations. Annotators are trained to apply your ontology consistently, respect guidelines for minimum box sizes, manage irregular shapes, and handle edge cases where boundaries are not clearly defined.Our teams annotate bounding boxes for robotics, autonomous driving, logistics, retail analytics, medical imaging, manufacturing inspection, smart cities, agriculture, and geospatial applications. We also support bounding box annotation in video, which requires frame to frame consistency, temporal tracking rules, and object identity stability.For sensitive datasets, DataVLab offers EU only annotation with GDPR aligned workflows. Whether you need bounding boxes for a proof of concept, a benchmarking dataset, or a large scale production pipeline, we provide reliable annotation quality with predictable turnaround times.