VAE architecture for the video compression

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diffusion model trained on videos and images of different durations, resolutions and aspect ratios. It also uses a Transformer architecture, which is a diffusion Transformer.  Technical report link: penai/research/video-generation-models-as-world-simulators words super complete dismantling | Sora prompt word cheats and comparison of the effects of competing products NVIDIA AI scientist Jim Fan believes that Sora should be a data-driven physics engine. Sora is a simulation of a real or fantasy world. It uses some denoising and gradient descent to learn


complex rendering, intuitive physics, long-shot reasoning and semantic Malaysia Phone Number Data foundations. Xie Saining, an assistant professor at New York University, believes that Sora will rewrite the entire field of video generation. Sora should be built on DiT, a diffusion Transformer. In short, DiT is a diffusion model with a Transformer backbone, which  [VAE encoder  ViT  DDPM  VAE decoder]. Xie Saining speculated that Sora may use the  network. The difference is that it has been trained on original video data. And since VAE is a ConvNet,





DiT is technically a hybrid model. () Visual data processing method Sora innovatively uses Patches technology to process visual data, which is different from the token processing method of large language models. By compressing the video content into a low-dimensional latent space and further deconstructing it into spatio-temporal patches, the video is converted into an easy-to-process patch form. words super complete dismantling | Sora prompt word cheats and comparison of the effects of competing products () Flexibility of video formats Sora can generate