3D Scene Generation with Scanned RGB-D data
Project Description
Indoor scene understanding requires a large amount of 3D data. However, building
such data takes a lot of efforts. In this project, we use scanned RGB-D data to
learn a generative model for these 3D scenes. The generative model can later be
used for data generation, scene understanding and human-assited design process.
such data takes a lot of efforts. In this project, we use scanned RGB-D data to
learn a generative model for these 3D scenes. The generative model can later be
used for data generation, scene understanding and human-assited design process.
Supervisor
YEUNG, Sai Kit
Quota
5
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles
Required Skill: basic C++/Python programming, computer graphics background is
preferred
preferred
Applicant's Learning Objectives
The students will learn about deep learning techniques for scene generation and
understanding. They will get training on data processing and how to build a 3D
application.
understanding. They will get training on data processing and how to build a 3D
application.
Complexity of the project
Moderate