PyTorch Face Recognizer based on 'VGGFace2: A dataset for recognising faces across pose and age'
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Updated
Jun 17, 2018 - Python
PyTorch Face Recognizer based on 'VGGFace2: A dataset for recognising faces across pose and age'
Deep Face Recognition in PyTorch
Detecting Autism Spectrum Disorder in Children With Computer Vision - Adapting facial recognition models to detect Autism Spectrum Disorder
An open-source toolkit which is full of handy functions, including the most used models and utilities for deep-learning practitioners!
In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert people that do not wear a mask when entering a building.
Computer vision web application, built to predict the age, race, and gender of all individuals present in an image. Trained using PyTorch on the VGGFace2 and UTKFace datasets
This project presents a full process of creating face-detection & face-recognition web-application service using deep_utils library
An implementation to clean large scale public face dataset
Developed a deep novel coupled profile to frontal face recognition network incorporating pose as an auxiliary information via attention mechanism (i.e., implemented a pose attention module).
This project showcases an advanced face verification system built using the FaceNet deep learning architecture. The model is trained to accurately identify and verify individuals based on their facial features.
Machine learning pipeline for hiding small children faces in pictures to conceal their identity and protect their privacy.
This is FUTURE 2.0! Now even a single picture of your face can predict your BMI without knowing your height & weight. Not even a single face, multiple faces can be deteced in a single pisture to predict the AGE, SEX & BMI of all the visible faces on that picture. Isn't that futuristic?
Image Classification Training Framework for Network Distillation
Face Identification with MTCNN and VGGFace2
Smart Glasses for Visually Impaired people: Deep learning based smart glasses to assist visually impaired users in recognizing people and objects. Responsibilities included data collection, implementation, and documentation of face recognition module.
Study on the impact of image resolution on AI-based age estimation using DeepFace and InsightFace.
Classifying Deepfake imges using Residual learning Architecture
Artificial Intelligence
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