Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01dn39x4655
Title: Celebrity Face Generation from Textual Descriptions
Authors: Caruntu, Beatrice
Advisors: Deng, Jia
Department: Computer Science
Class Year: 2021
Abstract: This paper details the creation of a new text and image paired data set from the CelebA image and attribute collection in order to facilitate a text-to-face image generation model. It also details the design, development, and evaluation of a text-conditioned Generative Adversarial Deep Convolutional Network. The most relevant steps taken in the project consist in assembling meaningful and accurate text captions for the CelebA dataset, the use of GloVe and EMLo embeddings, and recreating the GAN-CLS architecture in TensorFlow given its original paper and Pytorch Repository. The goal of this project is to generate text conditioned faces as accurately and as ”real” as possible and to gain a better insight into the effects of specific text embeddings on the final synthetic images.
URI: http://arks.princeton.edu/ark:/88435/dsp01dn39x4655
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Computer Science, 1988-2021

Files in This Item:
File SizeFormat 
CARUNTU-BEATRICE-THESIS.pdf2.63 MBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.