Conference item
Class-agnostic counting
- Abstract:
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Nearly all existing counting methods are designed for a specific object class. Our work, however, aims to create a counting model able to count any class of object. To achieve this goal, we formulate counting as a matching problem, enabling us to exploit the image self-similarity property that naturally exists in object counting problems.
We make the following three contributions: first, a Generic Matching Network (GMN) architecture that can potentially count any object in a class-a...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
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(Accepted manuscript, pdf, 3.2MB)
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- Publisher copy:
- 10.1007/978-3-030-20893-6_42
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Authors
Funding
Bibliographic Details
- Publisher:
- Springer, Cham Publisher's website
- Journal:
- 14th Asian Conference on Computer Vision (ACCV 2018) Journal website
- Volume:
- 11363
- Pages:
- 669-684
- Series:
- Lecture Notes in Computer Science
- Host title:
- ACCV 2018: Computer Vision – ACCV 2018
- Publication date:
- 2019-05-29
- Acceptance date:
- 2018-09-21
- DOI:
- ISSN:
-
0302-9743
- Source identifiers:
-
944830
- ISBN:
- 9783030208936
Item Description
- Keywords:
- Pubs id:
-
pubs:944830
- UUID:
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uuid:0700b0af-1b14-4f4e-a7bc-8f38e93b4a51
- Local pid:
- pubs:944830
- Deposit date:
- 2018-11-21
Terms of use
- Copyright holder:
- Springer Nature Switzerland AG
- Copyright date:
- 2019
- Notes:
- Copyright © 2019 Springer Nature Switzerland AG. This is the accepted manuscript version of the paper. The final version is available online from Springer at: https://doi.org/10.1007/978-3-030-20893-6_42
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