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Lifestyle, Special Report, Americas

Posted: 07 Jun 2022 18:24
by rezkaesold
Next, since videos are perceived as infinite continuous signals, one needs to develop an appropriate sampling scheme to use them in a practical framework. Finally, one needs to accordingly redesign the discriminator to operate in the new sampling pipeline. To solve the first issue, we develop positional embeddings with time-varying wave parameters which depend on motion information, sampled uniquely for different videos. This motion information is represented as a sequence of motion codes produced by a padding-less conv1d-based model. RNN’s instability when unrolled to large depths. To produce frames non-autoregressively. Next, we investigate the question of how many samples are needed to learn a meaningful video generator. Finally, since our model sees only 2-4 randomly sampled frames per video, it is highly redundant to use expensive conv3d-blocks in the discriminator, which are designed to operate on long sequences of equidistant frames. That’s why we replace it with a conv2d-based model, which aggregates information temporarily via simple concatenation and is conditioned on the time distances between its input frames.




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Re: Lifestyle, Special Report, Americas

Posted: 15 Mar 2023 04:22
by wangiskahn2