Automatically generating textured buildings using reconstructive and statistical methods
Name
1129384696-MIT.pdf
Size
7.54 MB
Format
Adobe PDF
Checksum (MD5)
d27f1e3acab715456601fe4c8773aeb9
Author(s)
Lee, Ka Wai,M. Eng.Massachusetts Institute of Technology.
Advisor(s)
Frédo Durand.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
Realistic 3D models of cities are extremely important for generating synthetic datasets for deep learning models. Current algorithms generate models of cities that are either monotonous, unrealistic, or must be specified with many procedural rules. In this thesis we present AutoCity, a system for generating realistic textured buildings given only the footprints of the buildings. AutoCity generates buildings using reconstructive and procedural methods, and then textures the buildings using a known adversarial neural network, FrankenGAN. We provide images of our output and extensive documentation on how the system can be run and extended.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 45-46).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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