Post by account_disabled on Jan 27, 2024 22:41:53 GMT -6
Google announced Lumiere: an AI video generator with one of the most advanced text-to-video models yet. The name Lumière is apparently a reference to the Lumiere brothers who in 1895 staged the first cinema. Just as film was a modern technology in the late 19th century, the name Lumière is once again associated with it. with something new and original. A rendering of Lumiere, released by Google, focuses on animals. A model can create a scene using text; the same way AI image generators work, the user can dream up any scenario they want to see a short video clip. However, the user can also use the image as a request. Google provided several examples: including some real photos, such as Joe Rosenthal's iconic photo of Raising the Flag ; "Soldiers Raising the United States Flag on a Windy Day" sees one of the most famous photographs of the 20th century suddenly come to life as soldiers struggle with a flag affected by the wind.
Raise the Flag Fax Lists Jim Rosenthal. Raise the Flag Jim Rosenthal . Also included in Lumiere is a “Video Stylization” setting that allows users to load a source video and then ask the AI-generating model for various element changes. For example, a running person can suddenly turn into a toy made of colorful bricks. Another feature that Google showed is "Cinemagraphs", where only a part of the image is animated, while the rest remains. "Video masking" is also included, which involves masking a portion of the image so that the portion can be changed at the user's request. Space-time diffusion model Lumiere with the "Space-Time U-Net" architecture, which generates the entire temporal duration of the video at once through a single pass in the model.
This elusive concept is apparently in contrast to existing video models that "synthesize distant keystrokes followed by fast temporal resolution - an approach that inherently makes it difficult to achieve global temporal consistency". As Ars Technica notes , this basically means that Lumiere can process the elements inside the video and how they move simultaneously. Other text-to-video models group things into small chunks or frames. Lumiere certainly seems like an upgrade from the Imagen model that Google promoted in 2022, but there's no telling if and when the AI video tool will be used. It is not clear what training data was used for Lumiere, Google only said in its article that "We train our T2V [text-to-video] model on a dataset containing 30 million videos and their text captions.
Raise the Flag Fax Lists Jim Rosenthal. Raise the Flag Jim Rosenthal . Also included in Lumiere is a “Video Stylization” setting that allows users to load a source video and then ask the AI-generating model for various element changes. For example, a running person can suddenly turn into a toy made of colorful bricks. Another feature that Google showed is "Cinemagraphs", where only a part of the image is animated, while the rest remains. "Video masking" is also included, which involves masking a portion of the image so that the portion can be changed at the user's request. Space-time diffusion model Lumiere with the "Space-Time U-Net" architecture, which generates the entire temporal duration of the video at once through a single pass in the model.
This elusive concept is apparently in contrast to existing video models that "synthesize distant keystrokes followed by fast temporal resolution - an approach that inherently makes it difficult to achieve global temporal consistency". As Ars Technica notes , this basically means that Lumiere can process the elements inside the video and how they move simultaneously. Other text-to-video models group things into small chunks or frames. Lumiere certainly seems like an upgrade from the Imagen model that Google promoted in 2022, but there's no telling if and when the AI video tool will be used. It is not clear what training data was used for Lumiere, Google only said in its article that "We train our T2V [text-to-video] model on a dataset containing 30 million videos and their text captions.