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Text-to-video model. A text-to-video model is a machine learning model that takes a natural language description as input and produces a video relevant to the input text. [1] Recent advancements in generating high-quality, text-conditioned videos have largely been driven by the development of video diffusion models. [2]
A video is generated in latent space by denoising 3D "patches", then transformed to standard space by a video decompressor. Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos.
Sora (text-to-video model) Categories: Language modeling. Machine learning task. Deep learning. Computer graphics. Artificial intelligence art. Video processing. Film and video technology.
The Text-Based Video (TBV) model is a particular case of the more general Video-Based Learning (VBL) model in which an instructor’s curriculum is fully covered by high-quality videos and texts. The aim of this study is to test the effectiveness of the TBV model by examining and comparing its two main components: Videos and texts.
VideoPoet is a large language model developed by Google Research in 2023 for video making. It can be asked to animate still images. The model accepts text, images, and videos as inputs, with a program to add feature for any input to any format generated content. VideoPoet was publicly announced on December 19, 2023.
A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks. In 2022, the output of state-of-the-art text-to ...
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