Conference item icon

Conference item

Learning the semantic structure of objects from Web supervision

Abstract:

While recent research in image understanding has often focused on recognizing more types of objects, understanding more about the objects is just as important. Recognizing object parts and attributes has been extensively studied before, yet learning large space of such concepts remains elusive due to the high cost of providing detailed object annotations for supervision. The key contribution of this paper is an algorithm to learn the nameable parts of objects automatically, from images obtain...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.1007/978-3-319-49409-8_19

Authors


More by this author
Department:
Oxford, MPLS, Engineering Science
More by this author
Department:
Oxford, MPLS, Engineering Science
Publisher:
Springer Publisher's website
Publication date:
2016-11-05
Acceptance date:
2016-08-12
DOI:
Pubs id:
pubs:656434
URN:
uri:e30bdc0e-4202-45a5-b764-e7ef9b601e0d
UUID:
uuid:e30bdc0e-4202-45a5-b764-e7ef9b601e0d
Local pid:
pubs:656434

Terms of use


Metrics



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

TO TOP