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  Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences

VidalMata, R. G., Scheirer, W. J., Kukleva, A., Cox, D., & Kuehne, H. (2021). Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences. In IEEE Winter Conference on Applications of Computer Vision (pp. 1238-1247). Computer Vision Foundation.

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VidalMata_Joint_Visual-Temporal_Embedding_for_Unsupervised_Learning_of_Actions_in_Untrimmed_WACV_2021_paper.pdf (Preprint), 3MB
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VidalMata_Joint_Visual-Temporal_Embedding_for_Unsupervised_Learning_of_Actions_in_Untrimmed_WACV_2021_paper.pdf
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These research 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.
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 Creators:
VidalMata, Rosaura G.1, Author
Scheirer, Walter J.1, Author
Kukleva, Anna2, Author           
Cox, David1, Author
Kuehne, Hilde1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              

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Language(s): eng - English
 Dates: 2021
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: VidalMata_WACV21
 Degree: -

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Title: IEEE Winter Conference on Applications of Computer Vision
Place of Event: Virtual
Start-/End Date: 2021-01-05 - 2021-01-09

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Title: IEEE Winter Conference on Applications of Computer Vision
  Abbreviation : WACV 2021
Source Genre: Proceedings
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Publ. Info: Computer Vision Foundation
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1238 - 1247 Identifier: -