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There are several architectures that have been used to create Text-to-Video models. Similar to Text-to-Image models, these models can be trained using Recurrent Neural Networks (RNNs) such as long short-term memory (LSTM) networks, which has been used for Pixel Transformation Models and Stochastic Video Generation Models, which aid in consistency and realism respectively. [31]
Artificially intelligent computer-aided design (CAD) can use text-to-3D, image-to-3D, and video-to-3D to automate 3D modeling. [64] AI-based CAD libraries could also be developed using linked open data of schematics and diagrams. [65] AI CAD assistants are used as tools to help streamline workflow. [66]
This is achieved by textual inversion, namely, finding a new text term that correspond to these images. Following other text-to-image models, language model-powered text-to-video platforms such as Runway, Make-A-Video, [13] Imagen Video, [14] Midjourney, [15] and Phenaki [16] can generate video from text and/or text/image prompts. [17]
Online video platforms allow users to upload, share videos or live stream their own videos to the Internet. These can either be for the general public to watch, or particular users on a shared network. The most popular video hosting website is YouTube, 2 billion active until October 2020 and the most extensive catalog of online videos. [1]
The following is a list of video editing software. The criterion for inclusion in this list is the ability to perform non-linear video editing. Most modern transcoding software supports transcoding a portion of a video clip, which would count as cropping and trimming. However, items in this article have one of the following conditions:
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