Exploiting temporal context in 2d to 3d human pose regression

Varga, Viktor and Véges, Márton: Exploiting temporal context in 2d to 3d human pose regression. Conference of PhD Students in Computer Science, (11). pp. 169-172. (2018)

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Abstract

A major drawback of end-to-end image to 3d pose estimation approaches is the abscence of rich, in-the-wild image datasets with 3d human pose annotation. In this paper we show, that splitting the task and solving the subproblems of image based 2d pose estimation and 2d-to-3d coordinate regression independently is a viable approach. What is more, we present a lightweight deep learning based model to perform 2d-to-3d human body pose regression that is able to exploit temporal information and thus improve the state of the art.

Item Type: Article
Event Title: Conference of PhD students in computer science (11.) (2018) (Szeged)
Journal or Publication Title: Conference of PhD Students in Computer Science
Date: 2018
Volume: 11
Page Range: pp. 169-172
Uncontrolled Keywords: Számítástechnika
Additional Information: Bibliogr.: p. 171-172. ; összefoglalás angol nyelven
Date Deposited: 2019. Nov. 04. 14:40
Last Modified: 2019. Nov. 04. 14:40
URI: http://acta.bibl.u-szeged.hu/id/eprint/61795

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