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 Implementation of the Interpretable Conditional Adversarial Autoencoder using LIME (ICASSP 2024)
A TensorFlow GAN model to transform input images based on target age
PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.
PyTorch Lightning implementation of Disney's face re-aging network (FRAN) paper.
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