2 code implementations • 29 Apr 2023 • Emmanuel Martinez, Roman Jacome, Alejandra Hernandez-Rojas, Henry Arguello
To surmount this limitation, we propose low-dimensional GAN (LD-GAN), where we train the GAN employing a low-dimensional representation of the {dataset} with the latent space of a pretrained autoencoder network.
no code implementations • 22 Sep 2022 • Emmanuel Martinez, Edwin Vargas, Henry Arguello
Specifically, we propose to jointly optimize an optical architecture for acquiring a single coded light field snapshot and a convolutional neural network (CNN) for estimating the disparity maps.