Object Detection Annotation Services for Accurate and Reliable AI Models

Object detection is one of the core tasks in computer vision, and high quality annotation is essential for training reliable detection models.

Annotating objects consistently requires precise rules for box placement, class selection, occlusions, scale variation, and edge cases.

DataVLab provides object detection annotation services designed for engineering teams that need accuracy and scalability. Our annotators specialize in detecting objects across robotics, autonomous mobility, smart cities, industrial inspection, healthcare imaging, agriculture, and retail.

They follow detailed class instructions that specify how to handle partially visible objects, crowded scenes, reflective surfaces, motion blur, and small objects. We support single class and multi class detection models. Tasks include bounding boxes, detection attributes, hierarchical classes, and object states. For video datasets, we annotate frame to frame detection with stable object identities and smooth temporal transitions. Quality control includes multi step review with checks for box tightness, class drift, and consistency across similar frames.

Sensitive datasets can be processed under GDPR aligned workflows with optional EU only annotation.