WebNov 20, 2024 · We present a hierarchical VAE that, for the first time, generates samples quickly while outperforming the PixelCNN in log-likelihood on all natural image … WebClockwork VAEs are deep generative model that learn long-term dependencies in video by leveraging hierarchies of representations that progress at different clock speeds. In …

Clockwork Variational Autoencoders for Video Prediction

WebFigure 2: Inference (left) and generative (right) models for the Clockwork VAE with a hierarchy of two latent variables with s 1 = 1 and s 2 = 2. The models are unrolled over four consecutive time steps but note that the graph continues towards t= 0 and t= T x. Blue arrows indicate parameter sharing between the inference and generative models. WebFeb 22, 2024 · Finally, we adapt the Clockwork VAE, a state-of-the-art temporal LVM for video generation, to the speech domain. Despite being autoregressive only in latent space, we find that the Clockwork VAE can outperform previous LVMs and reduce the gap to deterministic models by using a hierarchy of latent variables. Submission history teks pidato bahasa sunda tentang akhlak

Clockwork Variational Autoencoders - NASA/ADS

WebJan 27, 2024 · The files include: `clockwork-vae-s64-reconstruction-*` Four reconstructions using a two-layered Clockwork VAE trained with temporal resolution s=64. `clockwork … WebWhile existing video prediction models succeed at generating sharp images, they tend to fail at accurately predicting far into the future. We introduce the Clockwork VAE (CW-VAE), … WebCW-VAE (3 levels, factor 2) RSSM SVG-LP random Figure 1: Video prediction quality as a function of the dis-tance predicted. We show 4 versions of Clockwork VAE with temporal abstraction factors 2, 4, 6, and 8. Larger temporal abstraction directly results in predictions that re-main accurate for longer horizons. Clockwork VAE further teks pidato bulan sastra