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Thesis

Learning to understand large-scale 3D point clouds

Abstract:

Giving machines the ability to precisely perceive and understand the 3D visual world is the fundamental step to allow them to interact competently within our physical world. However, the research on large-scale 3D scene understanding and perception is still in its infancy, due to the complex geometrical structure of 3D shapes and limited high-quality data resources. Among various 3D representations, point clouds have attracted increasing attention due to its flexibility, compactness, and t...

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Division:
MPLS
Department:
Computer Science
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Oxford college:
St Hugh's College
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Oxford college:
St Hugh's College
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Oxford college:
St Hugh's College
Role:
Examiner
ORCID:
0000-0001-9022-7599
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Oxford college:
St Hugh's College
Role:
Examiner


More from this funder
Funder identifier:
http://dx.doi.org/10.13039/501100004543
Grant:
201803170259
Programme:
China Scholarship Council Award


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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