MANAGED COMPUTER VISION DATASET OPERATIONS
Careful work. Reliable training data.
Aimage Annotators provides managed image, video, temporal and LiDAR annotation, dataset QA, review, correction and validated delivery for AI, robotics and computer-vision teams.
A model’s performance depends on consistent, traceable ground-truth data. We operate as an extension of your dataset team—from guideline calibration and production through review, correction and export validation—so your engineers spend less time fixing labels and more time improving models.
FROM CALIBRATION TO VALIDATED DELIVERY
Choose one focused service or combine multiple annotation types within a managed workflow. We adapt to your taxonomy, edge cases, platform, output schema and acceptance criteria.
Accurate 2D object detection labels for images and video frames.
We draw tight, consistent boxes around vehicles, people, products, defects and other objects while following your class taxonomy, occlusion rules and minimum-size criteria.
Common applications: Object detection, autonomous mobility, surveillance and retail AI
Explore this serviceDetailed outlines for objects with irregular or complex boundaries.
Our annotators place precise polygon points around visible object edges for road features, damage areas, medical regions, buildings and other non-rectangular targets.
Common applications: Damage detection, aerial imagery, medical and industrial inspection
Explore this servicePixel-level masks for scene understanding and precise object separation.
We create semantic masks for entire classes and instance masks for individual objects, with careful attention to boundaries, overlaps, holes and partially hidden regions.
Common applications: Scene understanding, robotics, healthcare and autonomous systems
Explore this serviceStructured points that capture pose, shape and object geometry.
We annotate human joints, facial landmarks, object corners and custom keypoint schemas with visibility states and consistent skeleton connections where required.
Common applications: Pose estimation, behavior analysis, sports and facial AI
Explore this serviceReliable category, attribute and scene labels for large visual datasets.
We classify full images or regions using single-label, multi-label and hierarchical taxonomies, including attributes, quality flags and edge-case escalation.
Common applications: Content moderation, search, retail catalogs and dataset curation
Explore this serviceConsistent identities, actions and events across video sequences.
We maintain object tracks through movement and temporary occlusion, review interpolation, and label time-based actions or events with precise start and end points for model-ready video data.
Common applications: Robotics, physical AI, traffic analytics, maritime, security and behavior models
Explore this serviceSpatial labels for point clouds and synchronized camera data.
We place and refine 3D cuboids, assign object attributes and maintain temporal consistency across LiDAR sequences for perception and sensor-fusion workflows.
Common applications: Autonomous vehicles, robotics, mapping and smart infrastructure
Explore this serviceIndependent quality control for newly labeled or existing datasets.
Our reviewers check missed objects, class accuracy, geometry, track consistency and guideline compliance, then correct issues and report recurring error patterns.
Common applications: Pre-training validation, vendor audits and dataset improvement
Explore this serviceQUALITY YOU CAN TRACE
We treat annotation as part of your model-development process—not as a simple drawing task. Questions are logged, edge-case decisions are aligned, reviewer feedback is incorporated into production and outputs are checked before delivery.
Confirm annotation type, classes, volume, platform, output schema and acceptance criteria.
Complete a representative sample batch, surface ambiguities and align decisions before scale.
Annotate in controlled batches with ongoing communication, sampling and version awareness.
Check geometry, classes, missing objects, attributes and temporal consistency; correct recurring errors.
Verify export structure and agreed quality checks, then address final feedback promptly.
DOMAIN EXPERIENCE
Our team adapts annotation decisions to the context of your domain, from tiny vehicle defects and medical regions to crowded maritime scenes and dense point clouds. Select an industry to view an example.
ABOUT AIMAGE ANNOTATORS
Aimage Annotators is a specialized computer vision dataset operations company led by Hema Sekhar. We support AI, machine learning and robotics teams with scalable image, video, temporal and LiDAR annotation, plus dataset quality assurance.
Our working style is straightforward: learn the guidelines carefully, communicate early, document uncertain cases, review consistently and deliver data that is ready for training, validation or audit.
PRACTICAL DATASET INSIGHTS
Explore practical guidance on computer vision datasets, video annotation, Track IDs, interpolation, LiDAR, quality assurance and delivery.
YOUR PLATFORM OR OUR WORKFLOW
FREQUENTLY ASKED QUESTIONS
We can work with common formats including COCO JSON, YOLO TXT, CVAT XML and other client-defined exports. The final format is confirmed during project calibration.
Yes. We study your taxonomy, examples and edge cases, complete a calibration batch and align the team before production begins.
Projects use calibrated instructions, trained annotators, ongoing sampling and dedicated review. Where the platform and scope permit, we can report acceptance, rejection and correction trends so quality is traceable—not just claimed.
Yes. Our services cover 2D image annotation, frame-by-frame video tracking and 3D point-cloud or cuboid annotation workflows.
START WITH A RAPID CALIBRATION BATCH
Share your guidelines, sample characteristics, volume, preferred platform and timeline. We’ll assess the scope and propose a representative calibration batch before scaling.
Discuss your dataset