MTCNN_face_detection_alignment is an implementation of the “Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks” algorithm. The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts, and instructions for dependencies. Non-maximum suppression and bounding box regression at each stage. Online hard sample mining to improve training robustness.

Features

  • Joint detection + alignment in a cascaded three-stage network
  • Online hard sample mining to improve training robustness
  • Non-maximum suppression and bounding box regression at each stage
  • Support for landmark localization (e.g. eyes, nose, mouth)
  • Support code for both Linux and Windows Caffe backends
  • Flexible deployment (MATLAB / Caffe)

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License

MIT License

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Additional Project Details

Programming Language

MATLAB

Related Categories

MATLAB Computer Vision Libraries

Registered

2025-09-29