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)
Categories
Computer Vision LibrariesLicense
MIT LicenseFollow MTCNN Face Detection Alignment
Other Useful Business Software
Earn up to 16% annual interest with Nexo.
Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform.
Geographic restrictions, eligibility, and terms apply.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of MTCNN Face Detection Alignment!