University of Illinois Urbana-Champaign

GTAMesh Dataset: Semantic 3D Perception Dataset

Wang, Jiahong

This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.

Permalink

https://hdl.handle.net/2142/109144

Description

Title
GTAMesh Dataset: Semantic 3D Perception Dataset
Author(s)
Wang, Jiahong
Contributor(s)
Schwing, Alexander
Issue Date
2020-12
Keyword(s)
  • 3D dataset
  • synthetic dataset
  • 3D vision
  • single-view reconstruction
Abstract
Abundance in 2D segmentation datasets has enabled the training of accurate 2D perception models. However, collecting real-world 3D perception datasets is challenging and time-consuming, and therefore, 3D perception datasets are few and often contain limited categories of objects. In this project, we aim to collect a large-scale synthetic dataset, the GTAMesh dataset, containing annotations for 3D geometry of objects represented as meshes. To this end, we use the game engine GTA-V for collecting the data. The mesh information of variegated objects can be extracted by hooking into the rendering pipeline. We show some application cases and develop a temporal baseline model for 3D reconstruction to demonstrate the effectiveness of our dataset.
Type of Resource
text
Language
en
Permalink
http://hdl.handle.net/2142/109144
Sponsor(s)/Grant Number(s)
National Science Foundation's Major Research Instrumentation program, grant #1725729

Owning Collections

Senior Theses - Electrical and Computer Engineering PRIMARY
The best of ECE undergraduate research