Thesis
Advances in fine-grained visual categorization
- Abstract:
-
The objective of this work is to improve performance in fine-grained visual categorization (FGVC). In particular, we are interested in the large-scale classification between hundreds of different flower, bird, dog species. FGVC is challenging due to high intra-class variances caused by deformation, view angle, illumination and occlusion, and low inter-class variance since some categories only differ in detail that only experts notice. Applications include field guides, automatic image anno...
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Authors
Contributors
+ Zisserman, A
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
+ Lempitsky, V
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Bibliographic Details
- Publication date:
- 2015
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- Oxford University, UK
Item Description
- Language:
-
English
- Keywords:
- Subjects:
- UUID:
-
uuid:f5dc5e73-118b-470c-900b-b7fce1d85786
- Local pid:
-
ora:11613
- Deposit date:
-
2015-06-09
Terms of use
- Copyright holder:
- Chai, Y
- Copyright date:
- 2015
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