IT4343E | Computer Vision Project
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Updated
May 16, 2024 - Python
IT4343E | Computer Vision Project
Facial Attribute Recognition using the Transformer architecture, 91% on CelebA
A Collection of Variational Autoencoders (VAE) in PyTorch.
Project code that has been developed during the Udacity Deep Learning Nano Degree.
PyTorch implementation of various Variational Autoencoder models
Detects and extracts faces from the images from your gallery 👱♂️
This repository contains the code, models and corpus of the project "Generative Adversarial Networks for Text-to-Image Synthesis & Generation: A Comparative Analysis of Natural Language Processing models for the Spanish language".
Apply Thatcher illusion on a set of face photos
👦 Human head semantic segmentation
[CVPR 2021] A large-scale face image dataset that allows text-to-image generation, text-guided image manipulation, sketch-to-image generation, GANs for face generation and editing, image caption, and VQA
Trained a Variational AutoEncoder Model to reconstruct the image and then sampled the latent space in order to get newly generated face images
A Variational Autoencoder in PyTorch for the CelebA Dataset
This repository is related to a project of the Introduction to Numerical Imaging (i.e, Introduction à l'Imagerie Numérique in French), given by the MVA Masters program at ENS-Paris Saclay. It was entirely build from scratch and contains code in PyTorch Lightning to train and then use a neural network for image classification. We used it to creat…
A semantic segmentation for a human parsing task in Tensorflow Python
This repository inclused several applications of extracting and classifying features from face images.
Repo containing basic and advanced GAN implementations.
Using conditional variational autoencoders to manipulate the images
Consistency and Accuracy analysis on CelebA
Code and notebooks related to the paper: "Reconstructing Faces from fMRI Patterns using Deep Generative Neural Networks" by VanRullen & Reddy, 2019
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