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Cited by 189

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A Dual-Source Approach for 3D Pose Estimation from a Single Image

Open access
Yasin, Hashim, Iqbal, Umar, Kruger, Bjorn, Weber, Andreas, Gall, Juergen·2016·2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Abstract

One major challenge for 3D pose estimation from a single RGB image is the acquisition of sufficient training data. In particular, collecting large amounts of training data that contain unconstrained images and are annotated with accurate 3D poses is infeasible. We therefore propose to use two independent training sources. The first source consists of images with annotated 2D poses and the second source consists of accurate 3D motion capture data. To integrate both sources, we propose a dual-source approach that combines 2D pose estimation with efficient and robust 3D pose retrieval. In our experiments, we show that our approach achieves state-of-the-art results and is even competitive when the skeleton structure of the two sources differ substantially.

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Crossref · 10.1109/cvpr.2016.535

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Metadata

Authors
Yasin, H., Iqbal, U., Kruger, B., Weber, A., & Gall, J.
Venue
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Publisher
IEEE
Published
2016-06
Pages
4948-4956
ISSN
1063-6919 (ISSN-L)
OpenAlex
W2963013806
Cited by
189
References
1
FWCI
13.63
Type
conference paper
Language
en
Open access
green

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