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NeuralDiff: Segmenting 3D objects that move in egocentric videos

Abstract:

Given a raw video sequence taken from a freely-moving camera, we study the problem of decomposing the observed 3D scene into a static background and a dynamic foreground containing the objects that move within the scene. This task is reminiscent of the classic background subtraction problem, but is significantly harder because all parts of the scene, static and dynamic, generate a large apparent motion due to the camera large viewpoint change and parallax. In particular, we consider egocentri...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/3dv53792.2021.00099

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
New College
Role:
Author
ORCID:
0000-0003-1374-2858
Publisher:
IEEE Publisher's website
Pages:
910-919
Host title:
2021 International Conference on 3D Vision (3DV)
Publication date:
2022-01-06
Acceptance date:
2021-10-01
Event title:
9th International Conference on 3D Vision (3DV)
Event location:
Virtual Event
Event website:
https://3dv2021.surrey.ac.uk/
Event start date:
2021-12-01T00:00:00Z
Event end date:
2021-12-03T00:00:00Z
DOI:
EISBN:
978-1-6654-2688-6
EISSN:
2475-7888
ISSN:
2378-3826
ISBN:
978-1-6654-2689-3
Language:
English
Keywords:
Pubs id:
1233319
Local pid:
pubs:1233319
Deposit date:
2022-01-26

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