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Recurrent human pose estimation

Abstract:

We propose a ConvNet model for predicting 2D human body poses in an image. The model regresses a heatmap representation for each body keypoint, and is able to learn and represent both the part appearances and the context of the part configuration. We make the following three contributions: (i) an architecture combining a feed forward module with a recurrent module, where the recurrent module can be run iteratively to improve the performance; (ii) the model can be trained end-to-end and from s...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/FG.2017.64

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Oxford college:
Brasenose College
Role:
Author
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Name:
Engineering and Physical Sciences Research Council
Grant:
EP/M013774/1
Publisher:
Institute of Electrical and Electronics Engineers
Host title:
12th IEEE Conference on Automatic Face and Gesture Recognition
Journal:
12th IEEE Conference on Automatic Face and Gesture Recognition More from this journal
Publication date:
2017-06-01
Acceptance date:
2016-10-10
Event location:
Washington DC
DOI:
Pubs id:
pubs:684068
UUID:
uuid:f28ba2c9-b4fb-41b6-9927-79f38b4ce388
Local pid:
pubs:684068
Source identifiers:
684068
Deposit date:
2017-03-06

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