Tiny Video Networks
Keyword(s):
Automatic video understanding is becoming more important for applications where real-time performance is crucial and compute is limited. Yet, accurate solutions so far have been computationally intensive. We propose efficient models for videos - Tiny Video Networks - which are video architectures, automatically designed to comply with fast runtimes and, at the same time are effective at video recognition tasks. The Tiny Video Networks run at faster-than-real-time speeds and demonstrate strong performance across several video benchmarks. These models not only provide new tools for real-time video applications, but also enable fast research and development in video understanding. Code and models are available.
2014 ◽
Vol 7
(4)
◽
pp. 694
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2014 ◽
Vol 39
(5)
◽
pp. 658-663
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Simulation research on real-time performance of CAN bus based on distributed dynamic prior-ity queue
2011 ◽
Vol 25
(7)
◽
pp. 591-596
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2021 ◽
Vol 4
(1)
◽
pp. 1-15
Keyword(s):
Keyword(s):