Video anonymization by face detection
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Updated
Oct 13, 2024 - Python
Video anonymization by face detection
Official implementation of ID-unaware Deepfake Detection Model
Machine Learning project a case study focused on the interaction with digital characters, using a character called "Kaio", which, based on the automatic detection of facial expressions and classification of emotions, interacts with humans by classifying emotions and imitating expressions
Orcas , Classify your images by human faces.
This repo contains, training material, dlib implementation, tensorflow implementation and an own made complete system implementation with a parse-controller.
A Generated Face Dataset: AGFD-20K. A Realistic, High-resolution, Vary & Balanced face dataset, generated by stable diffusion.
動画に出てくる複数の顔にモザイクぼかし処理をかけます。
To generate new human faces using GANs.
This repository contains the code for face recognition using library face_recognition. This library is using HOG algorithm to identify the human faces.
It contains a trained model to detect the number of faces in the given photo.
Disaster is a face search system for disasters using dlib, face_recognition, flask and others and what is written in python. How can you find a loved one in the event of a disaster? Disaster allows you to search for the face of the person you are looking for from the video taken by the camera installed in the shelter.
映像中の顔に対して特定人物以外にぼかし処理をかける
This SmartBrain app / clarifai faces-recognition app
Image classification project using convolutional neural networks (CNNs) for recognizing dog breeds
A face recognition website where you can simply submit a photo and by using Clarifai's machine learning API, my website shows the number of human faces in that picture
This repository contains the source code for the training and testing of Imagen on a dataset containing human faces.
Visualization of various image data using Principal Component Analysis and t-SNE
Generating Realistic Human Faces with Generative Networks
Proposed a novel method for image quality enhancement using diffusion models
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