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Learning shared embedding representation of motion and text using contrastive learning
Title: | Learning shared embedding representation of motion and text using contrastive learning |
Authors: | Horie, Junpei Browse this author | Noguchi, Wataru Browse this author →KAKEN DB | Iizuka, Hiroyuki Browse this author →KAKEN DB | Yamamoto, Masahito Browse this author →KAKEN DB |
Keywords: | Multi-modal learning | Contrastive learning | Skeleton-based action recognition | Motion retrieval |
Issue Date: | 27-Dec-2022 |
Publisher: | Springer |
Journal Title: | Artificial life and robotics |
Volume: | 28 |
Issue: | 1 |
Start Page: | 148 |
End Page: | 157 |
Publisher DOI: | 10.1007/s10015-022-00840-0 |
Abstract: | Multimodal learning of motion and text tries to find the correspondence between skeletal time-series data acquired by motion capture and the text that describes the motion. In this field, good associations can realize both motion-to-text and text-to-motion applications. However, the previous methods failed to associate motion with text, taking into account details of descriptions, for example, whether to move the left or right arm. In this paper, we propose a motion-text contrastive learning method for making correspondences between motion and text in a shared embedding space. We showed that our model outperforms the previous studies in the task of action recognition. We also qualitatively show that, by using a pre-trained text encoder, our model can perform motion retrieval with detailed correspondences between motion and text. |
Rights: | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10015-022-00840-0. |
Type: | article (author version) |
URI: | http://hdl.handle.net/2115/91020 |
Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 山本 雅人
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