Synthetic Datasets for smarter and safer cars

01
Hyper real images indistingushable from reality
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Diverse dataset covering all scenarios and environments
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Agnostic to camera position - change anytime
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Scalable to all car models
Driver and Objects Position Inside cars

Enable safer cars by understanding driver position and adjusting air bag strength in case of a crash

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Segmentation Maps

Segmentation maps of humans as well as objects for better object identification

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Depth Map

Highly accurate depth maps to understand the distance from the camera as well as the surrounding objects

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3D Pose of Passengers

Understand possible user actions based on their pose inside the car

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KEY FEATURES

Scale and Accuracy driven datasets.

Privacy

No need to collect and annotate from real world where privacy is an issue for users

AI Scientist Friendly

Cleaned dataset with a friendly JSON format (coco or similar)

Diversity

Very diverse dataset not otherwise possible in real world. Iterate and get results quickly

Black Swan Events

Simulate events/ scenarios which are unsafe to replicate in real world

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AI for Smarter and Safer Cars

Millions of Images in <1 month

Cost similar or lower than manual annotation

Diversity in real time

Built for higher accuracy

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