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Synthetic Datasets for ADAS and Autonomous Driving

automotive training and validation data

Give Your Training Data An Edge

  • Autonomous Driving and ADAS Simulation Platform | ADAS simulation company, AV certification autonomous certification, ADAS certification Cognata simulated frame with 3D bounding box annotation
  • Autonomous Driving and ADAS Simulation Platform | ADAS simulation company, AV certification autonomous certification, ADAS certification Cognata simulated frame with 3D bounding box annotation
  • Autonomous Driving and ADAS Simulation Platform | ADAS simulation company, AV certification autonomous certification, ADAS certification Cognata simulated frame with 3D bounding box annotation

Find Your Perfect ML Dataset Solution

Today’s perception algorithms have made the advancement of AI
for automated driving a race for training data

Cognata synthetic data provides the quality enrichment needed
to thoroughly train modern deep neural networks (DNN)

Accuracy & Realism

Industry-leading realism with pixel-perfect annotated training data

Diversity

Diverse weather, lighting, surface, and object variation across global scenes

Scale

Cloud architecture for quick and cost-effective creation and delivery

Realistic Environments From Around The World

  • Photorealistic synthetic drivable conditions
  • Variable weather
  • Challenging lighting
  • Varied surfaces and degradation
  • Varied markings, unmarked roads and gore areas

Enriched To Your Needs

  • Traffic signs and traffic lights from around the world
  • Large catalog of props and infrastructure assets
  • Rich libraries of vehicles, pedestrians, and cyclists

Viewed From Any Sensor, Anywhere

  • Flexible placement and configuration
  • Easy comparison of sensor suites
  • Camera datasets including wide-angle and fisheye for automated parking systems perception training
  • Customized LiDAR datasets per different LiDAR manufacturers including scanning pattern customization and materials reflectivity
  • Customized Radar datasets including noise models
  • Deep learning based synthetic training data

Delivered With Perfect Ground Truth

  • Automatically-generated accurate annotations
  • 2D & 3D bounding boxes with attributes and classification for object that an autonomous system might encounter
  • Pixel-perfect semantic and instance segmentation datasets
  • Depth datasets
  • Comprehensive scene and object attributes

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