At last, 2020 is coming to an end. It was an unprecedented year that tested our collective resilience. But thanks to our great partners and customers, we were able to adjust smoothly to the new normal and are growing at a rapid pace – and hiring for multiple engineering positions.
But first, some exciting news to close out the year:
- Our co-founder and CTO Felix Heide was named Young Engineer of the Year at the AutoSens Awards for his contributions to the automotive industry.
- In case you missed it, we have joined Partners for Automated Vehicle Education (PAVE) to help raise public awareness about the real-world challenges that ADAS and Autonomous Vehicle perception systems face in difficult driving conditions, and the advanced technologies applied to address them.
Let’s look back at our highlights from these past 12 months
2 Major Awards
For the 4th time in a row, Algolux won an AutoSens Award. This time, our co-founder and CTO Felix Heide was named Young Engineer of the Year. The award recognizes an engineer under the age of 35, who is judged to have demonstrated great achievement and leadership within the ADAS and autonomous vehicle industry and research community. The jury included top technical experts, representative of the full supply chain from OEMs to academia.
And back in the Spring, our Eos Embedded Perception Software was recognized as the Most Innovative Use of Artificial Intelligence and Machine Learning in the Development of Autonomous Vehicles and Respective Technologies at the 2020 Tech.AD Awards.
14 Industry Conferences and Presentations
From CES to AutoSens, Tech.AD and Auto.AI, as well as the Embedded Vision Summit, 2020 was a busy year for us with 14 live presentations! And while we wish we could have met more people at those events, we were still able to connect virtually with many industry leaders.
And if you couldn’t catch us “live” in 2020, here’s one of our presentations from Auto.AI Europe where our VP Marketing and Strategic Partnerships Dave Tokic demonstrates how our novel embedded perception stack outperforms public and commercial vision systems (including Tesla’s latest OTA Model S Autopilot and Nvidia Driveworks).
9 Research Papers, Including 6 at CVPR
Our R&D team published no fewer than 9 research papers. 6 of them were accepted at CVPR – including 3 orals (acceptance rate < 5%):
- CVPR 2020
- Learning Rank-1 Diffractive Optics for Single-shot High Dynamic Range Imaging (Oral)
- Hardware-in-the-loop End-to-end Optimization of Camera Image Processing Pipelines (Oral)
- Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar
- Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather
- Single-shot Monocular RGB-D Imaging using Uneven Double Refraction (Oral)
- Defending Against Universal Attacks Through Selective Feature Regeneration
If you would like to join our research team, we are hiring!
8 Blog Posts, and 1 Case Study
Our most-read blog post this year was about Tesla’s Highway Autopilot. In that article, we compared Tesla’s accuracy with Eos’ – and demonstrated the robustness of our solution.
And a few months ago, we published a case study in which we showed that Eos is 38 to 55 mAP points more accurate in adverse imaging conditions than state-of-the-art models.
2 Major Product Announcements
2020 was also an exciting year from a product development standpoint.
A few months ago, we announced major performance and scalability breakthroughs for our Atlas Camera Optimization Suite. Indeed, we developed a new machine learning approach that automatically optimizes cameras to maximize computer vision accuracy. It can be applied for any vision task, such as object or free space detection, while also massively reducing effort and time vs. today’s approaches.
Thanks to Atlas, OEMs and Tier 1 suppliers can quickly improve vision system effectiveness, directly addressing safety concerns to help spur broader adoption. Learn more about Atlas.
And a few months later, we announced our next-generation Eos Embedded Perception Software. The expanded Eos portfolio leverages a new AI deep learning framework to massively improve system scalability, development costs, and robust accuracy for all operating conditions.
Delivering a comprehensive portfolio of perception capabilities with next-generation robustness and scalability, Eos provides vision systems teams with the quickest path to safe and reliable driver-assist and autonomy capabilities. Learn more about Eos.
1 new patent
A 4th patent was granted to Algolux regarding novel methods of enhancing machine perception, particularly for joint image processing and perception. Learn more.
Stay tuned for our next case study. We will examine how the Atlas Camera Optimization Suite was used to automatically maximize computer vision accuracy for a front-facing vision system from a leading automotive Tier 1, improving results by up to 48% within days.