Vidu

Vidu is China's first long duration, high consistency, and high dynamics, jointly released by BioDigital Technology and Tsinghua University.AI Video GenerationBig model.On April 27, 2024 atZhongguancun ForumpendingAnnounced at the Artificial Intelligence Pioneers Forum, July 30, 2024, Vidu goes live.

Technology Architecture and Core Advantages

Vidu utilizes the team's original Diffusion and Transformer fusion architecture, U-ViT, which combines the generative capabilities of the Diffusion model with the perceptual capabilities of the Transformer model, allowing Vidu to excel in video generation.Key technologies of the U-ViT architecture include:

1. ViT (Vision Transformer): Split the image into small chunks (called patches), then consider these patches as elements (tokens) in a sequence, and utilize the Transformer's self-attention mechanism to capture global dependencies of the image.
2. Diffusion technology: For generating coherent and realistic video content.
3. U-Net's long skip structure: i.e., jump connections that help connect low-level features and accelerate the training of the network.
4. Time and condition as new token: Input into the Transformer block along with the image patches enhances the model's control over the generation process.

Together, these technologies enable Vidu to generate HD video content of up to 16 seconds in length and up to 1080p resolution in a single click, with smooth and consistent video and no noticeable frame breaks.

Key Features

1. Long video generation: Generate HD videos up to 16 seconds long with one click, based on text descriptions or images.
2. Multi-camera generation: Supports the generation of videos containing a wide range of shots such as distant, close-up, medium, and close-up, which increases the sense of dynamism and viewability of the video.
3. spatio-temporal consistency: Maintain a high degree of consistency in the video generation process, ensuring smooth scene transitions and harmonization between elements.
4. Physical World Simulation: The ability to simulate real-world physical characteristics, such as lighting effects, object movement, etc., makes the generated video content more realistic.
5. Rich Imagination: In addition to simulating real-life scenarios, Vidu can create fictional images that don't exist in the real world, satisfying users' needs for creative expression.
6. multimodal fusion: It is expected to integrate information from multiple modalities, such as text and images, to generate richer and three-dimensional video content.

Usage Scenarios

Vidu is used in a wide range of scenarios, including but not limited to:

1. advertising marketing: Quickly create eye-catching advertising videos to increase brand awareness and product sales.
2. Educational Demonstrations: Visualize complex concepts in video form to improve teaching effectiveness and student interest.
3. social media: Produce personalized social media video content that attracts more attention and interaction.
4. Corporate Training: Produce professional training videos to increase employee learning interest and efficiency.

Fees and Operations

Vidu offers a variety of paid packages for users to choose from, as well as a free trial version that allows users to experience its basic functions without paying for them. In terms of operation, Vidu's interface is simple and clear. Users only need to follow the prompts to enter text descriptions, upload pictures or adjust relevant parameters to generate videos that meet their requirements. After the generation is completed, users can preview the video effect and choose to download it locally or share it on social platforms.

Experience and Feedback

Users generally report that Vidu's experience is excellent. Its interface is simple and clear, and its operation is easy to get started. At the same time, Vidu's video generation speed is very fast, and can generate high-quality video content in a short time. In addition, Vidu also supports a variety of video styles and templates to meet the user's personalized creation needs. However, some users also feedback that when generating some complex scenes, the details of the video still need to be strengthened.