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DeepMind launched their most powerful generative video model, Veo, similar to OpenAI's Sora, capable of producing high-quality 1080p videos with a maximum length of over 60 seconds, covering a variety of styles from realism to surrealism and animation.
Veo also has the ability to edit existing video via text commands, maintain visual consistency, and generate continuous video sequences. Veo can accurately capture the nuances and tone of cues, providing unprecedented creative control, understanding cues for various film effects, such as time-lapse photography or aerial shots of landscapes.
Key Features of Veo
Generate high-quality video
- High-resolution video: Veo can generate professional-quality videos in 1080p resolution and can be over a minute long.
- Multiple visual styles: Ability to apply various film and visual styles, such as time-lapse photography, aerial shots, etc., to meet the needs of different creators.
High-level understanding and visual semantics
To generate a coherent scene, a generative video model needs to accurately interpret textual cues and combine this information with relevant visual references. Veo’s deep understanding of natural language and visual semantics allows it to generate videos that closely follow the cues. It accurately captures the nuances and tone of phrases, and presents intricate details in complex scenes.
- Capture prompt details precisely: Veo can accurately understand the nuances and intonation of text prompts and translate them into corresponding video content.
- Visual semantic combination: By combining relevant visual references, a coherent scene that meets the prompt requirements is generated to ensure the consistency of the video content with the prompt.
Film Production Control
Veo provides powerful film production control functions, allowing users to perform a variety of flexible editing operations during the video production process.
- Input Video Editing: When users provide an input video and specific editing commands (such as adding kayaks to an aerial shot of the coastline), Veo can generate a new edited video based on these commands.
This feature allows users to perform a variety of editing operations on the original video, such as adding new elements, changing scene details, etc., to achieve higher creative expression.
- Mask Editing: Veo supports mask editing, which allows users to add mask areas to videos and combine them with text prompts to modify specific areas of the video. Mask editing allows users to precisely select and adjust certain parts of the video without affecting other parts. For example, if the user wants to change the color of a specific object in the video or add an element, just apply a mask to the object and enter the corresponding editing command.
- Combining images with text prompts: Prompt: Drone shot along the Hawaii jungle coastline, sunny day
Users can provide a reference image and combine it with text prompts to generate a video. Veo will generate the corresponding video content based on the image style and text prompts provided. This method allows users to set the visual style of the video through reference images, and use text prompts to specify specific content and effects. For example, a user can provide an image of a night city and enter the prompt "display fireworks over the city", and Veo will generate a night city video showing fireworks.
Input image:
Prompt:
Output Video:
Extending video length:
The model can also create video clips and stretch them to 60 seconds or longer. It can create video clips based on a single prompt or a series of prompts that together tell a story.
- Extend video length: Veo can extend video clips to more than 60 seconds, allowing users to generate a complete story from a single prompt or a series of prompts.
Frame-to-frame consistency
Maintaining visual consistency is a challenge for video generation models. People, objects, or even entire scenes may unexpectedly flicker, jump, or deform between frames, ruining the viewing experience.
- Reduce visual inconsistencies: Use state-of-the-art latent diffusion transformers technology to reduce flickering, jumping or distortion between video frames, maintaining visual consistency of characters, objects and scenes.
Efficient video generation
- Compressed Video Representations: Leveraging high-quality compressed video representations (also called latent variables) improves generation efficiency and quality while reducing the time required to generate videos.
Technical Foundation of Veo
- Built on years of research: Veo builds on years of research in generative video models, including Generative Query Network(GQN), DVD-GAN, Imagen-Video, Phenaki, WALT, VideoPoet and Lumiere, and also our Transformer architecture and Gemini.
- Detailed training data: To help Veo understand and execute prompts more accurately, the team added more detailed captions to each video in the training data. These detailed captions provide richer information to help the model better understand the relationship between the video content and the prompt. For example, the original brief description may only say "the person is walking", but with more details, it may describe "a man in red clothes walking through a busy street on a snowy day."
- Efficient performance optimization: To further improve performance, the Veo model uses high-quality compressed video representations (also called latent representations). These latent representations are highly compressed versions of the video that contain key information and features of the video. Using this approach not only improves the overall quality of video generation, but also significantly reduces the time required to generate videos. The compressed representation enables the model to process and generate videos more efficiently, thereby speeding up the generation process.
Responsible Design
- Content watermarking: Videos generated by Veo are watermarked using the SynthID tool to identify AI-generated content.
- Safety Filtering: Videos go through safety filters and memory checks during the production process to help mitigate privacy, copyright, and bias risks.
The tool isn’t yet widely released, but will be available to select creators on Google’s AI Test Kitchen website through VideoFX.
Case Studies of Veo
More details: https://deepmind.google/technologies/veo/
Queue registration: https://aitestkitchen.withgoogle.com/zh/tools/video-fx
- Author:KCGOD
- URL:https://kcgod.com/google-veo
- Copyright:All articles in this blog, except for special statements, adopt BY-NC-SA agreement. Please indicate the source!
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