Overview
AI-driven Video Quality Optimizer
DeepField-PQO is a next generation AI-based pre-processor that intelligently optimizes video data prior to the existing encoder in the transcoding workflow. The core of this technology is a proprietary AI model trained using a virtual encoding framework that evaluates perceptual quality using VMAF and optimizes compression while preserving visual fidelity. Going beyond perceptual quality preservation, the AI model is designed to remove redundant information while retaining critical visual details, intelligently adapting to the characteristics of the content. As a result, the same visual quality of content can be transmitted and stored using substantially less data. DeepField-PQO delivers massive cost savings and service quality improvements across industries where large-scale video data is essential, such as streaming services and cloud video platforms. As an innovative solution, it offers two core benefits: smoother, sharper video video experiences for end users, and significant bandwidth reduction with improved infrastructure efficiency for service providers.
Highlights
- Retrainable : To avoid over-reliance on VMAF, customers can request balanced quality metrics like PSNR, SSIM, and VMAF to align with their intended use when re-training the AI model.
- Codec-agnostic : Improvement in the coding efficiency is observed with any encoders regardless of the standards, settings, and implementation.
- Real-time processing : Due to its fast processing speed, DeepField-PQO can be applied to live streaming such as sports and concerts
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64-bit (x86) Amazon Machine Image (AMI)
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Version release notes
DeepField-PQO v1.0.0
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