Post by account_disabled on Jan 28, 2024 4:46:53 GMT
Image generation technology has advanced rapidly in recent years, but achieving coherent video rendering remains a challenge for modern AI models. However, Google has recently shown significant progress in this area and demonstrated significantly improved technology in the field of video production. Google introduced the company's latest AI model, Lumiere, for video creation. Google says that Lumiere is a significant improvement in video synthesis, as creating "realistic, varied and coherent motion" has always been one of the main challenges for AI-based video generation. Lumiere proposes a space-time diffusion model that may seem to solve - or try to solve - such a problem. Mountain View's latest foray into the AI generation business is good enough for text-to-video, image-to-video, and style generation.
Users can Fax Lists create an entirely new clip by typing a text query, providing a source image (regardless of how original, realistic, or edited that image is), or using a reference image as the target style. Lumiere uses the novel Space-Time U-Net architecture, which generates the entire video clip at once through a single pass in the AI model. Compared to existing models that synthesize keyframes for a single video, Lumiere's approach can produce modern text-to-video results with less weirdness than before. Additional features of Lumiere include Video Style, which transforms the source video into different materials, and Cinemagraphs, which provides a way to animate a limited and highlighted part of the source image. The video image feature can modify certain parts of the source video, such as changing the colors, materials or textures of the girl's dress.
As Google emphasizes in the official document , Lumiere can produce videos of "low resolution" of 1024 × 1024, which last no more than 5 seconds. Previous AI video models were able to generate longer videos, but Google claims that users preferred Lumiere's output to existing AI models. Mountain View says Lumiere was trained on a dataset containing 30 million videos and their text descriptions, although the source (or copyright status) of these 5-second videos is currently unknown. The Google researchers' paper highlights the potential "societal impact" of AI video-generating technology like Lumiere, saying the main goal of the model is to enable "new users" to produce visual content in new creative and flexible ways. New tools to detect biases and "harmful" use cases of video generating models should be developed as soon as possible so as not to spoil the fun.
Users can Fax Lists create an entirely new clip by typing a text query, providing a source image (regardless of how original, realistic, or edited that image is), or using a reference image as the target style. Lumiere uses the novel Space-Time U-Net architecture, which generates the entire video clip at once through a single pass in the AI model. Compared to existing models that synthesize keyframes for a single video, Lumiere's approach can produce modern text-to-video results with less weirdness than before. Additional features of Lumiere include Video Style, which transforms the source video into different materials, and Cinemagraphs, which provides a way to animate a limited and highlighted part of the source image. The video image feature can modify certain parts of the source video, such as changing the colors, materials or textures of the girl's dress.
As Google emphasizes in the official document , Lumiere can produce videos of "low resolution" of 1024 × 1024, which last no more than 5 seconds. Previous AI video models were able to generate longer videos, but Google claims that users preferred Lumiere's output to existing AI models. Mountain View says Lumiere was trained on a dataset containing 30 million videos and their text descriptions, although the source (or copyright status) of these 5-second videos is currently unknown. The Google researchers' paper highlights the potential "societal impact" of AI video-generating technology like Lumiere, saying the main goal of the model is to enable "new users" to produce visual content in new creative and flexible ways. New tools to detect biases and "harmful" use cases of video generating models should be developed as soon as possible so as not to spoil the fun.