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Long Video Understanding Benchmark

Towards long-form video understanding. We propose a two-stream spatio-temporal attention network for long video classification which combines the advantages of convolutional inductive bias with the computational advantages of transformer networks.

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Cite this as

Chao-Yuan Wu, Philipp Krahenbuhl (2024). Dataset: Long Video Understanding Benchmark. https://doi.org/10.57702/plafsryv

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Author	Chao-Yuan Wu
More Authors	Philipp Krahenbuhl
Homepage	https://arxiv.org/abs/2106.02036