AlBahar, Badour A. Sh A.2023-06-092023-06-092023-06-08vt_gsexam:37466http://hdl.handle.net/10919/115382Computer 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.ETDenIn CopyrightComputer visionComputer graphicImage-to-image translationPose transferHuman reposingVideo editingDissertation