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Virginia Tech

Controllable Visual Synthesis

Abstract

dc:description.abstract

Computer graphics has become an integral part of various industries such as entertainment (i.e.,films and content creation), fashion (i.e.,virtual try-on), and video games. Computer graphics has evolved tremendously over the past years. It has shown remarkable image generation improvement from low-quality, pixelated images with limited details to highly realistic images with fine details that can often be mistaken for real images. However, the traditional pipeline of rendering an image in computer graphics is complex and time- consuming. The whole process of creating the geometry, material, and textures requires not only time but also significant expertise. In this work, we aim to replace this complex traditional computer graphics pipeline with a simple machine learning model. This machine learning model can synthesize realistic images without requiring expertise or significant time and effort. Specifically, we address the problem of controllable image synthesis. We propose several approaches that allow the user to synthesize realistic content and manipulate images to achieve their desired goals with ease and flexibility.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Computer Engineering
Department dc:contributor.department
Electrical and Computer Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • AlBahar, Badour A. Sh A.
Chairs dc:contributor.committeechair
  • Abbott, Amos L.
  • Huang, Jia-Bin
Committee members dc:contributor.committeemember
  • Dhillon, Harpreet Singh
  • Lourentzou, Ismini
  • Jia, Ruoxi
  • Wang, Ting-Chun

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:37466
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/115382

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

AlBahar, Badour A. Sh A.. Controllable Visual Synthesis. doctoral thesis, Virginia Tech, 2023. http://hdl.handle.net/10919/115382