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Video synopsis combines a visual summary of stored video together with an indexing mechanism. When a summary is required, all objects from the target period are collected and shifted in time to create a much shorter synopsis video showing maximum activity. A synopsis video clip is generated, in real time, in which objects a
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
Replacing YouTube links: Most link removals are uncontested, and the removed links are not replaced, but somewhere between 1% and 10% of links are replaced, often with discussion of why the link was valuable/not copyvio/etc. That discussion sometimes occurs on the article talk page, and sometimes occurs on the user talk page of the editor who ...
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For example: Videos often contain less information than alternative websites or the Wikipedia article itself. This concern limits use of many videos according to ELNO#1. Adding links to gratis online videos that promote a site or product may be considered spam. Inclusion of such a link is only acceptable if it refers to the official site ...
Fellow video essayist Thomas Flight observes videos about popular media receiving more clicks as part of the video essay economy. [21] In 2017, Sight & Sound, the magazine published by the British Film Institute (BFI), started an annual polls of the best video essays of the year. The 2021 poll reported that 38% of the essayists whose work ...
Invidious is a free and open-source alternative frontend to YouTube. [2] [3] It is available as a Docker container, [4] or from the GitHub master branch. [5]It is intended to be used as a lightweight and "privacy-respecting" alternative to the official YouTube website. [2]
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]