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Keras implementation of the renowned publication "DeepFace: Closing the Gap to Human-Level Performance in Face Verification" by Taigman et al. Pre-trained weights on VGGFace2 dataset.

Home Page: https://research.fb.com/publications/deepface-closing-the-gap-to-human-level-performance-in-face-verification/

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deepface's Introduction

DeepFace

Open source implementation of the renowned publication titled "DeepFace: Closing the Gap to Human-Level Performance in Face Verification" by Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, Lior Wolf published at Conference on Computer Vision and Pattern Recognition (CVPR) 2014.

DeepFace (CVPR14) Network Architecture

Implementation of this paper have been done using Keras (tf.keras). This project and necessary research was supported by the TensorFlow Research Cloud (TFRC). GCP resources have been used to train a million-scale machine learning model using Cloud TPUs.

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