Beamr’s Benchmark Testing Validates ML-Safe Video Data Workflows for Autonomous Vehicles
Testing demonstrates 48% file size reduction with robust ML model accuracy across multiple industry-standard metrics. AV teams are invited to meet Beamr at CES 2026, January 6-9 in Las Vegas
Herzliya, Israel, Dec. 22, 2025 (GLOBE NEWSWIRE) — Beamr Imaging Ltd. (NASDAQ: BMR), a leader in video optimization technology and solutions, published benchmark testing results validating that its patented Content-Adaptive Bitrate (CABR) technology delivers up to 50% storage reduction for autonomous vehicle (AV) video data with comprehensive technical demonstration of machine learning (ML) model accuracy.
AV teams and developers attending CES 2026 in Las Vegas, from January 6-9, 2026, are invited to schedule a meeting with Beamr’s video data experts to review the results and discuss ML-safe AV pipelines. To schedule a meeting at CES 2026, visit this link.
The new testing addresses a critical challenge in AV development: balancing the need to reduce massive amounts of real-world and synthetic video data while maintaining the fidelity required for accurate ML model performance. AV systems produce hundreds of petabytes of multi-camera footage, creating substantial costs in budget and infrastructure.
“AV teams need proven approaches to manage video data at scale without risking their ML pipeline integrity,” said Beamr Chief Product Officer, Dani Megrelishvili. “The benchmark testing validates that transformation is possible with confidence – less than 2% model accuracy impact while achieving significant compression efficiency.”
The benchmark testing compared Beamr’s CABR technology against industry-standard workflows using PandaSet, a real-world, multi-camera AV dataset. The validation focused on object detection, a foundational task for AV perception systems, deploying a YOLOv8 (Nano) model on both baseline and CABR-compressed videos. The analysis measured model accuracy across the most prevalent classes in the AV industry: persons, cars, motorcycles, and trucks.
Results showed CABR achieved approximately 48% average file size reduction with less than 2% difference in mean Average Precision (mAP), a standard metric for object detection reliability. The testing confirmed robust results across multiple other industry-standard quality metrics, such as PSNR and LPIPS.
The complete benchmark testing methodology and results are available in Beamr’s blog post.
To schedule a meeting at CES 2026, visit this link.
About Beamr
Beamr (Nasdaq: BMR) is a world leader in content-adaptive video compression, trusted by top media companies including Netflix and Paramount. Beamr’s perceptual optimization technology (CABR) is backed by 53 patents and a winner of Emmy® Award for Technology and Engineering. The innovative technology reduces video file sizes by up to 50% while preserving quality and enabling AI-powered enhancements.
Beamr powers efficient video workflows across high-growth markets, such as media and entertainment, user-generated content, machine learning, and autonomous vehicles. Its flexible deployment options include on-premises, private or public cloud, with convenient availability for Amazon Web Services (AWS) and Oracle Cloud Infrastructure (OCI) customers.
For more details, please visit www.beamr.com or the investors’ website www.investors.beamr.com
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