Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks

MTCNN Face Detection & Alignment

face detection and alignment with mtcnn

End-to-end MTCNN face detection and alignment workflow with reproducible PyTorch implementation.

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks

No description available

MTCNN face detection & alignment all in TensorFlow

Face Detection and Alignment using Multi-task Cascaded Convolutional Networks (MTCNN)

MTCNNfor face detection and alignment（人脸检测&对齐 究极版）

No description available

No description available

MTCNN-TensorFlow - Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks based Counting

This study presents a novel method for predicting cardiac disease by integrating a 2D CNN with an MTCNN for accurate face feature detection and alignment in medical images. By harnessing deep learning's ability to extract features, our framework offers a non-invasive, effective approach to early cardiovascular diagnosis and intervention.

Face Detection and Alignment-68 using MTCNN

A Keras implementation of MTCNN from [Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks](https://kpzhang93.github.io/MTCNN_face_detection_alignment/paper/spl.pdf)

No description available

No description available

MTCNN

Pure c++ implementation of MTCNN_face_detection_alignment

No description available

MTCNN face detection and alignment tools

Efficient face detection and alignment tool with MTCNN

MTCNN-TensorFlow - Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

Using MTCNN and various pre-processing techniques to optimise Face Detection and Alignment for Face Recognition.

This work is used for reproduce MTCNN,a Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks.

This project aims to develop a deepfake detection engine leveraging Multi-Task Cascaded Convolutional Networks (MTCNN) for face detection and alignment, and InceptionResnetV1, provided by the facenet_pytorch library, for image classification

Face detection and one-to-one verification using MTCNN for bounding boxes/keypoints and FaceNet embeddings with cosine similarity, plus alignment utilities, threshold tuning, and evaluation (confusion matrix, ROC); research/education only.

This repository implements a face grouping system that automatically clusters photos of the same person, similar to how Google Photos works. It uses a hybrid embedding approach by combining multiple pretrained models ArcFace, FaceNet, SFace, VGG-Face with MTCNN alignment for consistent face detection.

A minimal and production-friendly deep learning face recognition pipeline built with PyTorch and facenet-pytorch. This repo provides face detection & alignment (MTCNN), embedding extraction (InceptionResnetV1 pretrained on VGGFace2), and a simple SVM classifier for identity recognition. Includes CLI toolS

The project focuses on detecting deepfake images using transfer learning with MobileNetV2 fine-tuned on a dataset of real and fake images. MTCNN is used for face detection and alignment. Data augmentation techniques are applied to increase dataset diversity. The deepfake detection model consists of MobileNetV2,Dense layers for binary classification