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Predicting Video with VQVAE
[article]
2021
arXiv
pre-print
In recent years, the task of video prediction-forecasting future video given past video frames-has attracted attention in the research community. In this paper we propose a novel approach to this problem with Vector Quantized Variational AutoEncoders (VQ-VAE). With VQ-VAE we compress high-resolution videos into a hierarchical set of multi-scale discrete latent variables. Compared to pixels, this compressed latent space has dramatically reduced dimensionality, allowing us to apply scalable
arXiv:2103.01950v1
fatcat:fmbirgg4bnh25akw2nm2yfnxjm