Autonomous vehicle data annotation

Jul 7 – Oct 19, 2026Updated Oct 19, 2026Reviewed by

How we measure

AI summary

holds a narrow lead over for image segmentation datasets used to build self-driving cars.

Which brands AI mentions

#BrandMentioned in
#1tiedBasicAI62%
#1tiediMerit57%
#1tiedLabelbox50%
#1tiedScale50%

High-speed, API-driven labeling with AI pre-labeling and human verification

#5tiedAppen43%

Large-scale autonomous-driving imagery and multimodal camera and LiDAR annotation

Mentioned in

ChatGPTChatGPTGoogle AI ModeGoogle AI Mode

Widest split: Labelbox, 29% on ChatGPT and 71% on Google AI Mode.

  • #1tiedBasicAIChatGPT 67%Google AI Mode 57%
  • #1tiediMeritChatGPT 38%Google AI Mode 76%
  • #1tiedLabelboxChatGPT 29%Google AI Mode 71%
  • #1tiedScaleChatGPT 57%Google AI Mode 43%
  • #5tiedAppenChatGPT 48%Google AI Mode 38%

Questions and answers

  • ChatGPTOct 10, 2026

    1. 1TELUS Digital
    2. 2Deepen AI
    3. 3BasicAI
    4. 4Segments.ai
    5. 5Kognic
    6. 6Agiliway

    For a self-driving car dataset, you have several good options for image segmentation annotation services, including providers that offer pixel-level semantic segmentation, instance segmentation, video labeling, and 3D LiDAR annotation.

    I would start with providers specializing in automotive perception rather than general-purpose image labeling, especially if your dataset includes roads, lanes, sidewalks, vehicles, cyclists, pedestrians, and drivable areas.

    Recommended annotation providers

    • AI-Assisted Semantic Segmentation Labeling | Scale AI

    1. TELUS Digital

    (Best for large-scale projects)

    Managed annotation services for automotive AI, including pixel-level segmentation, long-sequence video annotation, and 2D/3D sensor fusion. Suitable for large datasets with enterprise quality and security requirements.

    Website:

    • スバル、AI開発拠点を渋谷に開設…アイサイトとAIの融合を加速 | レスポンス（Response.jp）

    2. Deepen AI

    (Best for 2D + LiDAR)

    Offers managed annotation services for images, video, and 3D point clouds, including semantic and instance segmentation, object tracking, and multi-sensor labeling. Its in-house team handles specialized automotive work.

    Website:

    • Perception

    3. BasicAI

    Provides image segmentation, 2D/3D bounding boxes, lane markings, LiDAR annotation, and sensor fusion for autonomous vehicles and ADAS. A good candidate for a customized automotive labeling workflow.

    Website:

    • Segments.ai: Reviews, Pricing & Free Demo - Software Finder - 2026

    4. Segments.ai

    Offers semantic segmentation tools, AI-assisted mask creation, pre-labeling, and optional outsourced annotation. Particularly attractive if your engineering team wants to automate part of the labeling workflow and retain control over review.

    Website:

    • Active Learning Annotation Solutions for Autonomous Driving | Kognic

    5. Kognic

    Specializes in autonomous-driving annotation across cameras, LiDAR, and radar. Offers managed services, a platform license, and hybrid deployments for teams that need specialized multi-sensor labeling.

    Website:

    • Autonomous Vehicles – SuperAnnotate Solutions

    6. Agiliway

    Provides manual image and video annotation for automotive AI, including semantic and instance segmentation, road surfaces, lane boundaries, obstacles, and other road-scene objects. Worth considering for a custom labeling engagement.

    Website:

    How to choose for your dataset

    Your requirementProviders to shortlist
    Large-scale outsourced labelingTELUS Digital, Deepen AI
    Pixel-accurate road-scene segmentationBasicAI, Deepen AI, Agiliway
    Camera + LiDAR segmentationDeepen AI, TELUS Digital, Kognic
    AI-assisted annotation and engineering controlSegments.ai
    Managed service plus in-house toolingKognic, TELUS Digital

    These are capability-based recommendations, not independently benchmarked rankings. Request a pilot before committing to a large contract.

    What to ask vendors before selecting one

    • Segmentation type: Do you support semantic, instance, and panoptic segmentation?
    • Quality: Can you report class-level IoU, boundary accuracy, and inter-annotator agreement?
    • Driving-specific edge cases: How do you handle occlusion, night scenes, rain, construction zones, and unusual road users?
    • Consistency: Can you propagate labels across video frames and keep object IDs consistent?
    • Delivery: Do you support your required formats, such as COCO, PNG masks, or your own schema?
    • Commercial terms: What are the per-image or per-frame costs, minimum volumes, turnaround times, and rework policies?
    • Data security: Can you meet your requirements for confidentiality, access control, retention, and data residency?

    My recommendation: Start with TELUS Digital and Deepen AI if you need a fully managed service. Include Segments.ai if you want your own team to operate an annotation platform. Have each candidate label the same representative sample of your dataset and compare quality, cost, and turnaround.

    Sources cited in this answer8

    Google AI ModeOct 10, 2026

    1. 1Scale
    2. 2iMerit
    3. 3Labelbox
    4. 4SuperAnnotate
    5. 5TELUS Digital
    6. 6Appen

    For building self-driving car datasets that require precise pixel-level understanding (such as semantic segmentation, instance segmentation, and lane/road geometry mapping), several established enterprise data annotation companies and platforms specialize in autonomous vehicle (AV) workflows.

    Leading providers offering image segmentation and computer vision annotation services for the automotive industry include:

    • Scale AI : A dominant enterprise AI data platform providing managed data labeling and infrastructure tailored heavily toward autonomous vehicles, robotics, and multi-sensor fusion (camera, LiDAR, radar).
    • iMerit : Known for high-accuracy computer vision and perception annotation, they feature dedicated automotive AI centers of excellence handling complex semantic and instance segmentation for autonomous mobility.
    • Labelbox : Offers a robust collaborative data-centric AI platform equipped with advanced annotation tools, automation features, and managed services for dense image and video segmentation tasks.
    • SuperAnnotate : Started with a strong core focus on high-precision image segmentation tools and workflows, making it ideal for pixel-level ground truth creation.
    • TELUS Digital : Provides extensive AI data solutions, including specialized computer vision annotation and large-scale global workforce support for autonomous driving programs.
    • Appen : A massive global data provider leveraging a large contributor network and tooling to manage multi-modal annotation needs, including polygon and semantic image segmentation.

    If you'd like to narrow down the choice, please share:

    • Are you looking for a fully managed service (outsourced workforce) or a software platform to power your in-house team?
    • Do you also need sensor fusion (combining camera images with LiDAR point clouds)?

    Sources cited in this answer4

  • Our "human-in-the-loop" review process is too slow. Who offers AI-assisted labeling interfaces to speed up annotators?

    Summary

    Several providers are cited for AI-assisted labeling, including Scale, SuperAnnotate, and Labelbox. No single brand is the usual answer.

Also asked as

  • We are working on self-driving car technology and need help annotating our datasets. Which providers offer specialized labeling services for this?
  • Can you recommend companies that handle image segmentation labeling for self-driving car projects?