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ByteDance's OmniHuman-1 model is able to create realistic videos of humans talking and moving naturally from a single still image, according to a paper published by researchers with the tech ...
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]
Dream Machine is a text-to-video model created by Luma Labs and launched in June 2024. It generates video output based on user prompts or still images. Dream Machine has been noted for its ability to realistically capture motion, while some critics have remarked upon the lack of transparency about its training data.
Compositing, image overlays, watermarks When arranging clips in a video project, images on the higher tracks/layers will be displayed on top, and the lower tracks will be displayed behind them. Much like a stack of paper, items on top cover up items below them. And if you cut any holes out (i.e. transparency) the lower images will show though.
Animoto was founded in August 2006 by Jason Hsiao, Brad Jefferson, Stevie Clifton and Tom Clifton because of the poor video quality found on the internet. [5] Animoto’s patented Cinematic Artificial Intelligence technology allows users to turn photos, video clips and music into video slideshows. [6]
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