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Why physics matters ?
Reproducing the physics of light accurately
However, for the case of self-driving vehicles or any other autonomous system, this assumption cannot be held, as people show extremely low tolerance to mistakes made by artificial intelligence.
It’s becoming evident that high AI robustness and safety levels cannot be achieved exclusively by real-world data training.
They can produce visually appealing images and sequences though they typically sacrifice physical accuracy in favor of real-time performance — a must for a video game.
Strong sun glares caused by wet surfaces, car lights scattered through fog or heavy rain, traffic lights diffracted by tiny water drops on the lens of the camera, traffic lights reflected in water ponds or glass facades and blurred by motion, are just few examples of complex visual conditions where the AI could be easily cheated.
Save time & costs - Simulate sensors!
Physically-based sensor simulation to train, test, and validate your computer perception deep learning model
About Anyverse™
Anyverse™ helps you continuously improve your deep learning perception models to reduce your system’s time to market applying new software 2.0 processes. Our synthetic data production platform allows us to provide high-fidelity accurate and balanced datasets. Along with a data-driven iterative process, we can help you reach the required model performance.
With Anyverse™ you can accurately simulate any camera sensor and help you decide which one will perform better with your perception system. No more complex and expensive experiments with real devices, thanks to our state-of-the-art photometric pipeline.
Need to know more?
Come visit our booth during the event, our website anyverse.ai anytime, our Linkedin, Facebook, and Twitter social media profiles.
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