06-08-2022, 05:57 AM
Unfortunately, the flurry of press over Sputnik I caused Nikita Khrushchev, head of the Communist Party, to rush Sputnik 2 to launch for the one-month "anniversary" of Sputnik I, and designs for the new satellite were very poor. The Soviets even admitted soon after the launch that Laika wouldn't return home, and the satellite itself burned up in reentry. Officials led people to believe the dog survived in orbit for as long as four days before she died from overheating. In 2002, however, evidence revealed Laika actually passed away just a few hours after the launch from a combination of heat and panic. Laika's death encouraged Americans to talk more openly about the treatment of animals, and the Russian people looked down upon Sputnik 2 as an unfortunate attempt at propaganda. For lots more information on exploration, discovery and living organisms in space, see the next page. Are chimpanzees evolving in the wild? Is there a difference between monkeys and apes? Bushnell, David. "History of research in space biology and biodynamics." NASA History Division. Gray, Tara. "A brief history of animals in space." NASA History Division.|Video summarization aims to automatically generate a summary (storyboard or video skim) of a video, which can facilitate large-scale video retrieving and browsing. Most of the existing methods perform video summarization on individual videos, which neglects the correlations among similar videos. Such correlations, however, are also informative for video understanding and video summarization. To address this limitation, we propose Video Joint Modelling based on Hierarchical Transformer (VJMHT) for co-summarization, which takes into consideration the semantic dependencies across videos. Specifically, VJMHT consists of two layers of Transformer: the first layer extracts semantic representation from individual shots of similar videos, while the second layer performs shot-level video joint modelling to aggregate cross-video semantic information. By this means, complete cross-video high-level patterns are explicitly modelled and learned for the summarization of individual videos. Moreover, Transformer-based video representation reconstruction is introduced to maximize the high-level similarity between the summary and the original video. Extensive experiments are conducted to verify the effectiveness of the proposed modules and the superiority of VJMHT in terms of F-measure and rank-based evaluation.
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