FaceNet: A Unified Embedding for Face Recognition and Clustering

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Publications: arXiv Add/Edit

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Despite significant recent advances in the field of face recognition, implementing face verification and recognition efficiently at scale presents serious challenges to current approaches. In this paper we present a system, called FaceNet, that directly learns a mapping from face images to a compact Euclidean space where distances directly correspond to a measure of face similarity. Once this space has been produced, tasks such as face recognition, verification and clustering can be easily implemented using standard techniques with FaceNet embeddings as feature vectors. Our method uses a deep convolutional network trained to directly optimize the embedding itself, rather than an intermediate bottleneck layer as in previous deep learning approaches. To train, we use triplets of roughly aligned matching / non-matching face patches generated using a novel online triplet mining method. The benefit of our approach is much greater representational efficiency: we achieve state-of-the-art face recognition performance using only 128-bytes per face. On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99.63%. On YouTube Faces DB it achieves 95.12%. Our system cuts the error rate in comparison to the best published result by 30% on both datasets. We also introduce the concept of harmonic embeddings, and a harmonic triplet loss, which describe different versions of face embeddings (produced by different networks) that are compatible to each other and allow for direct comparison between each other.

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Code Links

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Face recognition using Tensorflow

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Face recognition using Tensorflow

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train tools for Facenet

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mxnet version batch hard triplet loss

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This is an implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering.

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Deep learning face detection and recognition, implemented by pytorch. (pytorch)

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A FaceNet based face verification model, which validates a claimed identity based on the image of a face, and either accepts or rejects the identity claim (one-to-one matching).

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github.com: /M155K4R4/facenet

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Real-time face detection and recognition using deep learning

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face recognition python work

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Using SigComp'11 dataset for signature verification

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Voice Biometrics Authentication using GMM and Face Recognition Using Facenet and Tensorflow

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A loss function based on the distances between anchor, positive and negative embeddings used in FaceNet

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NN1 network from FaceNet: A Unified Embedding for Face Recognition and Clustering, in Keras.

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A face recognition application developed in JavaScript. It is a collaborative work of our project team.

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Solve face verification, recognition and clustering problems: A TensorFlow backed FaceNet implementation for Node.js.

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Bi thc hnh 1 - MachineLearning

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github.com: /Anil1331/Facenet

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VRPWRP (Vision-algorithms Requests Processing Wrappers), a pip package for running deep-learning Computer Vision algorithms from the cloud.

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PyTorch implementation of the paper "FaceNet: A Unified Embedding for Face Recognition and Clustering"

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Notes from the DeepLearning.AI courses

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github.com: /Maninder10/face

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A neural net trained over a person's personal photo collection to do face detection

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Face recognition using Facenet Model

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Deep Learning Models for Vision Tasks on iOS

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A light weight face recognition implementation using a pre-trained facenet model

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顔パスプロジェクト

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TripletLoss criterion for Chainer

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Identify humpback whale based on its fluke

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Implementation of facial recognition using facenets.

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Facial Recognition using Facenet

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NN1 network from FaceNet: A Unified Embedding for Face Recognition and Clustering, in Keras.

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Face Classify and Detection

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ConvNet for face recognition

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Add the triplet loss layer and the corresponding data layer to an exited network(i.e., AlexNet) by Python

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A PyTorch implementation of the Facenet model for face recognition. A port of facenet-darknet-inference to PyTorch.

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https://arxiv.org/pdf/1503.03832.pdf - Pytorch

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Master Piece

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Getting a Application of face detection by Faster R-CNN & Facenet Architecture

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Just creating real time face recognition with facenet

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TensorFlow implementations of some deep learning papers

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Implementing Face recognition using Facenet Method(Siamese network) using pre trained weights from deeplearning.ai's repo.

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github.com: /tbmoon/facenet

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FaceNet for face recognition using pytorch

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This is a face recognition system for personal house use.

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