Google revealed the new version of its large linguistic model for producing videos known as VideoPoet, designed to perform a variety of tasks including converting text into video, image into video, and video into audio.
VideoPoet tackles the challenge of creating coherent and cohesive movements in video clips, which is considered a challenge in current video production technologies.
This new model stands out for integrating multiple capabilities for video generation within a single large linguistic model, compared to current models that rely on a fragmented approach to capabilities.
The model is utilized through various methods and is trained using distinctive tokens, such as MAGVIT V2 for video and images, and SoundStream for audio.
With this feature, VideoPoet can perform a variety of tasks, such as animating images and editing and designing video clips based on input data from the text.
VideoPoet emerges as a significant development in the advanced scene of video generation technology using artificial intelligence, standing out from current models like Imagen Video, RunwayML, Stable Video Diffusion, Pika, and Animate Anywhere, with its enhanced capabilities in text accuracy and motion rhythm.
This new model excels over similar models by precisely following textual demands and producing engaging video clips with attractive movements.
Google’s new model stands out in producing content more effectively by using minimal inputs, such as a single text message or image, without the need for specific training on this content.
The VideoPoet application offers a high level of accuracy in converting written content into video, unlike other applications that may struggle to create large coherent movements, enhancing user experience.
Other models often face challenges in producing large coherent flaw-free movements, whereas Google’s new model shows a noticeable improvement in this area, resulting in the production of dynamic and seamless video clips.
