![]() It establishes a metric 3D space and uses the face landmark screen positions to estimate a face transform within that space. Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance critical for live experiences.Īdditionally, the solution is bundled with the Face Transform module that bridges the gap between the face landmark estimation and useful real-time augmented reality (AR) applications. It employs machine learning (ML) to infer the 3D facial surface, requiring only a single camera input without the need for a dedicated depth sensor. MediaPipe Face Mesh is a solution that estimates 468 3D face landmarks in real-time even on mobile devices. This site uses Just the Docs, a documentation theme for Jekyll. YouTube-8M Feature Extraction and Model Inference.AutoFlip (Saliency-aware Video Cropping).KNIFT (Template-based Feature Matching). ![]()
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