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Learning Actions From the Web
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Date
2009-01-01
Author
İKİZLER CİNBİŞ, NAZLI
Cinbiş, Ramazan Gökberk
Sclaroff, Stan
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This paper proposes a generic method for action recognition in uncontrolled videos. The idea is to use images collected from the Web to learn representations of actions and use this knowledge to automatically annotate actions in videos. Our approach is unsupervised in the sense that it requires no human intervention other than the text querying. Its benefits are two-fold: 1) we can improve retrieval of action images, and 2) we can collect a large generic database of action poses, which can then be used in tagging videos. We present experimental evidence that using action images collected from the Web, annotating actions is possible.
URI
https://hdl.handle.net/11511/56800
DOI
https://doi.org/10.1109/iccv.2009.5459368
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Department of Computer Engineering, Conference / Seminar
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N. İKİZLER CİNBİŞ, R. G. Cinbiş, and S. Sclaroff, “Learning Actions From the Web,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56800.