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SF-Net: Single-Frame Supervision for Temporal Action Localization

This paper proposes a method for temporal action localization using single-frame supervision. The authors use a unified system called SF-Net to predict actionness scores and mine pseudo action and background frames.

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Cite this as

Fan Ma, Linchao Zhu, Yi Yang, Shengxin Zha, Gourab Kundu, Matt Feiszli, Zheng Shou (2025). Dataset: SF-Net: Single-Frame Supervision for Temporal Action Localization. https://doi.org/10.57702/65l6es0b

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Additional Info

Field	Value
Created	January 2, 2025
Last update	January 2, 2025
Defined In	https://doi.org/10.48550/arXiv.2003.06845
Author	Fan Ma
More Authors	Linchao Zhu Yi Yang Shengxin Zha Gourab Kundu Matt Feiszli Zheng Shou
Homepage	https://github.com/Flowerfan/SF-Net