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Events

first seen date

2024-09-21 23:01:52

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created at

2024-09-21 23:01:52

updated at

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Open Graph

title

description

image

site name

author

updated

2026-02-20 08:02:03

raw text

SpeedNet: Learning the Speediness in Videos   SpeedNet: Learning the Speediness in Videos Sagie Benaim Ariel Ephrat Oran Lang Inbar Mosseri William T. Freeman Michael Rubinstein Michal Irani Tali Dekel Given an input video, our method automatically predicts the "speediness" of objects in the video-—whether they move faster, at, or slower than their natural speed. Right: a video of a dancer alternates between normal speed and slow motion play-back, as correctly captured by our speediness prediction over time. The core component of our method is SpeedNet (left)-—a novel deep network that can detect whether an object is moving at, or faster than, its normal speed. Abstract We wish to automatically predict the "speediness" of moving objects in videos---whether they move faster, at, or slower than their "natural" speed. The core component in our approach is SpeedNet---a novel deep network trained to detect if a video is playing at normal rate, or if it is sped up....

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