A deep learning model to age faces in the wild, currently runs at 60+ fps on GPUs
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Updated
May 18, 2024 - Python
A deep learning model to age faces in the wild, currently runs at 60+ fps on GPUs
Pytorch Implementation of the Explainable Conditional Adversarial Autoencoder using Saliency Maps and SHAP (J. of Imaging - MDPI)
Age Progression/Regression by Conditional Adversarial Autoencoder
PyTorch Lightning implementation of Disney's face re-aging network (FRAN) paper.
A TensorFlow GAN model to transform input images based on target age
Pytorch Implementation of the Interpretable Conditional Adversarial Autoencoder using LIME (ICASSP 2024)
Face Aging Webapp, using Flask and Only a Matter of Style
PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.
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