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  Physical Inertial Poser (PIP): Physics-Aware Real-Time Human Motion Tracking From Sparse Inertial Sensors

Yi, X., Zhou, Y., Habermann, M., Shimada, S., Golyanik, V., Theobalt, C., et al. (2022). Physical Inertial Poser (PIP): Physics-Aware Real-Time Human Motion Tracking From Sparse Inertial Sensors. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 13157-13168). Piscataway, NJ: IEEE. doi:10.1109/CVPR52688.2022.01282.

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Genre: Konferenzbeitrag
Latex : {Physical Inertial Poser (PIP)}: {P}hysics-Aware Real-Time Human Motion Tracking From Sparse Inertial Sensors

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Yi_Physical_Inertial_Poser_PIP_Physics-Aware_Real-Time_Human_Motion_Tracking_From_CVPR_2022_paper.pdf (beliebiger Volltext), 3MB
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Yi_Physical_Inertial_Poser_PIP_Physics-Aware_Real-Time_Human_Motion_Tracking_From_CVPR_2022_paper.pdf
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These CVPR 2021 papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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 Urheber:
Yi, Xinyu1, Autor
Zhou, Yuxiao1, Autor
Habermann, Marc2, Autor           
Shimada, Soshi2, Autor           
Golyanik, Vladislav2, Autor           
Theobalt, Christian2, Autor                 
Xu, Feng1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2Visual Computing and Artificial Intelligence, MPI for Informatics, Max Planck Society, ou_3311330              

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Sprache(n): eng - English
 Datum: 2022
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: Yi_CVPR22
DOI: 10.1109/CVPR52688.2022.01282
 Art des Abschluß: -

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Titel: 35th IEEE/CVF Conference on Computer Vision and Pattern Recognition
Veranstaltungsort: New Orleans, LA, USA
Start-/Enddatum: 2022-06-19 - 2022-06-24

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Titel: IEEE/CVF Conference on Computer Vision and Pattern Recognition
  Kurztitel : CVPR 2022
Genre der Quelle: Konferenzband
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Ort, Verlag, Ausgabe: Piscataway, NJ : IEEE
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 13157 - 13168 Identifikator: ISBN: 978-1-6654-6946-3