April 15, 2022, 1:12 a.m. | Ivan Skorokhodov, Sergey Tulyakov, Mohamed Elhoseiny

cs.LG updates on arXiv.org arxiv.org

Videos show continuous events, yet most $-$ if not all $-$ video synthesis
frameworks treat them discretely in time. In this work, we think of videos of
what they should be $-$ time-continuous signals, and extend the paradigm of
neural representations to build a continuous-time video generator. For this, we
first design continuous motion representations through the lens of positional
embeddings. Then, we explore the question of training on very sparse videos and
demonstrate that a good generator can be …

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