Conference item icon

Conference item

Unsupervised intuitive physics from visual observations

Abstract:

While learning models of intuitive physics is an active area of research, current approaches fall short of natural intelligences in one important regard: they require external supervision, such as explicit access to physical states, at training and sometimes even at test time. Some approaches sidestep these requirements by building models on top of handcrafted physical simulators. In both cases, however, methods cannot learn automatically new physical environments and their laws as humans do....

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

Actions


Access Document


Files:
Publisher copy:
10.1007/978-3-030-20893-6_44

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
New College
Role:
Author
Publisher:
Springer, Cham Publisher's website
Volume:
11363
Pages:
700-716
Series:
Lecture Notes in Computer Science
Publication date:
2019-05-29
Acceptance date:
2018-11-08
DOI:
ISSN:
0302-9743
Pubs id:
pubs:942831
URN:
uri:db3a04e0-7748-4e43-87f7-42c465961245
UUID:
uuid:db3a04e0-7748-4e43-87f7-42c465961245
Local pid:
pubs:942831
ISBN:
978-3-030-20893-6

Terms of use


Metrics


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP