Image and Video Annotation for innovative Computer Vision applications
COMPUTER VISION
Your trusted partner in Computer Vision
Digital Divide Data’s (DDD) computer vision team and technology partners allow us to offer a wide range of image and video annotation services including bounding boxes, polygons, semantic and instance segmentation, polylines, keypoints, and more. We have specialty teams with deep domain experience in key industries like Autonomous Driving, Agricultural Robotics, Retail / eCommerce and more.
Using traditional providers and platforms
can cost you 60% of your time.
CV Annotation Types
We support a full complement of CV annotation types
Bounding Box
Cuboid
Polygon
Keypoint
Instance
Segmentation
Polyline
Semantic Segmentation
Object Tracking
Object tracking requires not only detecting objects but accurately distinguishing and following objects across video frames. Object tracking use cases include shopper behavior, surveillance, sports analytics, traffic control, autonomous vehicles and others.
Object Detection
Numerous Computer Vision use cases depend on Object Detection to locate and identify pertinent objects in images or videos, including robotics, autonomous vehicles, food harvesting, surveillance, inventory control, and others.
Classification
Image Classification is a CV task that involves interpretation, ascertaining whether an image or video meets particular criteria. Classification has broad applications, including visual search, product recommendations, telemedicine, and law enforcement.
Semantic Segmentation
Semantic Segmentation assigns every pixel in an image or video to any of a number of salient classes (e.g., vehicle, pedestrian, traffic sign, road, building, sky). Semantic Segmentation features prominently in models involving autonomous vehicles, aerial surveying, emissions regulation, and others.
Instance Segmentation
A pixel-level identification of each instance of an object in an image or video. Use cases where Instance Segmentation is beneficial include surveillance, robotic navigation, law enforcement, livestock management, and others.
Learn how we can help with your Computer Vision programs
Training Data Considerations
Expert Training Data Pipeline for Computer Vision and Natural Language Processing
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The DDD Difference
Strategic
We are more than a data labeling service. We bring industry-tested SMEs, provide training data strategy, and understand the data security and training requirements needed to deliver better client outcomes.
Reliable
Our global workforce allows us to deliver high quality work, 365 days a year, across 100’s and 1000’s of data labelers across multiple countries and time zones. With 24/7 coverage, we are agile in responding to changing project needs.
Consistent
We are lifetime project partners. Your assigned team will stay with you - no rotation. And as your team becomes experts over time, they train more labelers. That's how we achieve scale.
Flexible
We are platform agnostic. We don't force you to use our tools, we integrate with the technology stack that works best for your project.
Secured, for ease of mind
Data and information security is a mission critical business function at DDD. Our clients depend on us to keep their valuable and confidential information secure, and we take this responsibility seriously.
Frequently Asked Questions (FAQ)
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We provide a full suite of data annotation services tailored for computer vision applications, including image annotation services, video annotation services, and AI data annotation services. Our capabilities span bounding boxes, polygons, semantic segmentation, instance segmentation, keypoints, polylines, and more, designed to suit a wide range of use cases in autonomous vehicles, robotics, retail, and surveillance.
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High-quality annotations are critical for training reliable AI models. As a trusted data labeling company, we deliver pixel-precise, scalable annotations to power object detection, semantic segmentation, classification, and more. Our team ensures consistency and accuracy across datasets, enabling efficient training of models in real-world conditions.
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Unlike generic data annotation companies, DDD combines deep domain expertise with a human-in-the-loop approach for agile delivery at scale. Our computer vision experts and curated workforce specialize in complex annotation types like instance segmentation, panoptic segmentation, and lidar annotation, with proven experience in verticals such as autonomous driving, agricultural robotics, and e-commerce.
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We offer 3D annotation solutions such as cuboids and LiDAR annotation, which are essential for applications in autonomous vehicles, mapping, and robotics. Our teams are trained to work with depth data and point clouds, ensuring high spatial accuracy.
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Absolutely. As one of the top data labeling companies, we’re equipped to manage high-volume projects without compromising on quality or speed. We employ a scalable workforce and quality assurance pipelines to meet the demands of enterprises and AI training data companies alike.
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We serve a variety of sectors, including:
Autonomous Vehicles – for object detection deep learning and semantic segmentation
Retail & E-commerce – for visual search, inventory management
Agriculture – for plant/fruit detection using polygon annotation
Security & Surveillance – for people and object tracking
Healthcare – for image classification and segmentation in diagnostics
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Yes. We can integrate with your existing ML pipelines, labeling tools, or APIs. Our flexible delivery model and tool-agnostic approach support custom workflows and QA feedback loops.
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Semantic Segmentation assigns a class to every pixel (e.g., "car" or "tree"), useful for general object identification.
Instance Segmentation goes a step further by differentiating between individual objects of the same class (e.g., car 1 vs. car 2).
Both are crucial for high-precision tasks in autonomous systems, and we support both types natively.