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Anyverse and Cron AI join forces to improve LiDAR simulation accuracy

Anyverse and Cron AI join forces to improve LiDAR simulation accuracy

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September 5, 2022

Anyverse announced today its collaboration with Cron AI, the cutting-edge 3D data perception platform for autonomous machines. Cron AI selected Anyverse hyperspectral synthetic data generation platform to provide the most accurate LiDAR synthetic data and ensure consistent neural network training on all possible corner cases that real-world data may have missed.

Cron AI identified the need to use simulation as a cornerstone of its long-term data strategy, especially for applications that demand perception accuracy in extremely diverse environments and sensor configurations. Cron AI’s adaptative 3D data perception platform senseEDGE uses deep learning at its core which poses the challenge of collecting truly diverse data for various applications (intelligent transport systems, smart spaces, robotics applications, autonomous vehicles, and security).

The search for a lidar simulation technology partner truly fitting our needs was long and full of disappointments. Pretty pictures and perfect-looking point clouds do not equal good training data. We are very happy to have partnered with Anyverse, who understood these problems and were ready to pioneer lidar simulation for neural network training that truly works in the wild.

Robert De Temple

Principal Director, Perception Software & Deep Learning at Cron AI

Anyverse’s sensor-specific synthetic data allows them to overcome these limitations in the datasets, especially for many hard-to-find corner cases of object types, poses, and distributions as well as to leverage perfectly labeled, complex object attributes that are impossible to annotate by hand. It also provides them with unique opportunities to generate highly project-specific data at scale for novel environments or sensor models before they have any access to them.

Having a tight collaboration like the one with Cron AI is key for Anyverse to improve its simulation platform. In this case, a long-term relationship will help advance Anyverse’s LiDAR simulation capabilities in a way that wouldn’t be possible without Cron AI expertise in the field and first hand feedback to provide a more accurate simulation in the near future.

Javier Salado

Technical Product Manager at Anyverse

New case study releasing soon!

This is a long-term collaboration that began more than a year ago. Anyverse and Cron AI have been working closely since then on their first project and this September will share some exciting insights in the form of a new case study. Follow Anyverse and Cron AI on Linkedin if you don’t want to miss this release or any other exciting news.

About Cron AI

Cron AI is powering the autonomy revolution with senseEDGE™ – its robust, adaptive, 3D data perception platform.

This unique plug-and-play, deep learning, first 3D perception platform harnesses the power of edge-efficient artificial intelligence to bring accuracy, universal performance, and reduce lifetime costs across mobility and intelligent transport systems, smart spaces, security, and robotics use.

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.

Looking to start your Synthetic Data journey or need help with your current project? We'd love to know more.

Looking for the right Synthetic Data to speed up your system? Please, enter the Anyverse now

Client Story

Would you like to know how Cron AI has improved LiDAR simulation accuracy with physically correct synthetic data?

Let's talk about synthetic data!

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