The SeetaFace Recognition Engine includes the three core modules required to build a fully automated face recognition system, namely the Face Detection Module SeetaFace Detection, the Face Feature Point Segment Module SeetaFace Alignment, and the Face Feature Extraction and Matching Module SeetaFace Identification. The main function:  Face Detection Module (SeetaFace Detection): A combination of traditional artificial features and multi-layer sensor (MLP) cascade structure, in the FDDB reached 84.4 recall rate (100 false detection), and Can process VGA resolution images in real time on a single i7 CPU.  Face feature positioning module (SeetaFace Alignment): by cascading multiple depth model (stack self-coding network) to return to five key feature points (two centers, nose and two mouth) position, in the AFLW To achieve the state-of-the-art accuracy, positioning speed in a single i7 CPU more than 200fps.  Face Recognition Module (SeetaFace Identificat

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