Recognizing Fine-grained and Composite Activities Using Hand-centric Features 
and Script Data

Rohrbach, Marcus; Rohrbach, Anna; Regneri, Michaela; Amin, Sikandar; Andriluka, Mykhaylo; Pinkal, Manfred; Schiele, Bernt

doi:10.1007/s11263-015-0851-8

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Recognizing Fine-grained and Composite Activities Using Hand-centric Features and Script Data

Rohrbach, M., Rohrbach, A., Regneri, M., Amin, S., Andriluka, M., Pinkal, M., et al. (2016). Recognizing Fine-grained and Composite Activities Using Hand-centric Features and Script Data. International Journal of Computer Vision, 119(3), 346-373. doi:10.1007/s11263-015-0851-8.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0028-D56A-2 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002C-1F1C-D

Genre: Journal Article

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Creators:
Rohrbach, Marcus¹, Author
Rohrbach, Anna¹, Author
Regneri, Michaela², Author
Amin, Sikandar¹, Author
Andriluka, Mykhaylo¹, Author
Pinkal, Manfred², Author
Schiele, Bernt¹, Author

Affiliations:
1Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society, ou_1116547
2External Organizations, ou_persistent22

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Language(s): eng - English

Dates: Accepted: 2015-07-13Published Online: 2015-08-22Date issued: 2016

Publication Status: Issued

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Identifiers: DOI: 10.1007/s11263-015-0851-8
BibTex Citekey: rohrbach15ijcv

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Title: International Journal of Computer Vision

Other : Int. J. Comput. Vis.

Source Genre: Journal

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Publ. Info: New York, NY : Springer

Pages: 22 p. Volume / Issue: 119 (3) Sequence Number: - Start / End Page: 346 - 373 Identifier: ISSN: 0920-5691
CoNE: https://pure.mpg.de/cone/journals/resource/954925564668