A comparison is made on MNIST dataset with softmax regression function layer and SVM layer as a classification layer with 2 layers and 3 layers SAE (Stack Autoencoders) respectively. Experimental ...

and various variational autoencoders for unsupervised latent representation learning from 2D and 3D images, primarily focusing on MRIs. This repository was developed as part of the paper titled ...

Official implementation of 'Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders'.

Abstract: In this research, we present a new method on how to reconstruct 3D object from 2D images by employing Variational Autoencoders (VAE ... our approach learns the distribution of 3D shapes ...