![]() All of these works try to select frames based on a saliency measure to keep the maximal “information” from the original video, or minimal camera jitter in the case of first-person videos. An important task is of intelligent fast-forwarding of regular videos, or egocentric videos, where frames are selected to preserve the gist of the video, while allowing the user to view it in less time. perform query-based adaptive video speedup-frames similar to the query clip are played slower, and different ones faster. use a measure of “frame importance” based on motion saliency estimation, to select important frames. The early seminal work of Bennett and McMillan calculates an optimal non-uniform sampling to satisfy various visual objectives, as captured by error metrics defined between pairs of frames. This idea was explored by several papers. Our variable speedup technique produces non-uniform temporal sampling of the video frames. ![]() ), then the walking segments do indeed get recognized as faster-than-normal human motions (higher speediness scores), whereas the static segments (no person in the scene), are classified as normal speed. If we input to SpeedNet the video played at twice the speed ( 2 × The magnitude of motions varies significantly throughout the sequence (in particular, the motions get larger when the person is closer to the camera middle plot), but our SpeedNet model is able to produce a stable classification of normal speed throughout the video (speediness score close to zero). A person is walking back and forth, at first further away from the camera, then closer to the camera (top). The model is trained on Kinetics, a large corpus of natural videos of human actions, in a self-supervised manner, without requiring manual labels. We then show how this basic binary classification model can be applied at test time to predict arbitrary rates of speediness in videos, when objects are sped-up, or slowed-down, by different factors (Fig. ![]() We dub this the “speediness” of the object. Typical to videos that are sped up uniformly. Viewers to watch videos faster, but with less of the jittery, unnatural motions SpeedNet for generating time-varying, adaptive video speedups, which can allow Recognition, and can be used for video retrieval. How those learned features can boost the performance of self-supervised action Space-time representation that goes beyond simple motion cues. Predicting the speed of videos, the model learns a powerful and meaningful Videos containing complex natural motions, and examine the visual cues it We demonstrate prediction results by SpeedNet on a wide range of We show how this single, binaryĬlassification network can be used to detect arbitrary rates of speediness of Without requiring any manual annotations. Is trained on a large corpus of natural videos in a self-supervised manner, To detect if a video is playing at normal rate, or if it is sped up. The core component in our approach is SpeedNet-a novel deep network trained Videos-whether they move faster, at, or slower than their "natural" speed. These animated files are ideal for quick comments, meme formats, and in-text video embeds.We wish to automatically predict the "speediness" of moving objects in You can remove the background of a video, for example, and add a different background to convert to a funny GIF to share with friends. Kapwing also supports a large library of text animations as well as special effects that you can apply to your GIF. Remember that animated GIFs will not play sound, so converting a video into a GIF will remove any sound from the video file. ![]() Go further as to add text, transitions, animations, images, crops, filters, and speed adjustments to enhance your content. Simply paste the YouTube video link to make a GIF out of a video or upload multiple images and adjust the time duration of your GIF. Using this GIF maker, you can make GIFs from YouTube or your own images in seconds. Make GIFs for Instagram, Discord, Twitter, and Reddit to share perfect reacts to post, strengthen your own tone, or highlight your online personality. With Kapwing's online GIF editor, creators can now easily make GIFs from videos, images, or even just text. GIFs have become an essential part of our every day language. Brilliantly capture the little moments of emotion and reaction.
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