18400856. GENERATING VIDEOS USING SEQUENCES OF GENERATIVE NEURAL NETWORKS simplified abstract (Google LLC)
GENERATING VIDEOS USING SEQUENCES OF GENERATIVE NEURAL NETWORKS
Organization Name
Inventor(s)
Jonathan Ho of New York NY (US)
Chitwan Saharia of Toronto (CA)
Jay Ha Whang of Austin TX (US)
GENERATING VIDEOS USING SEQUENCES OF GENERATIVE NEURAL NETWORKS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18400856 titled 'GENERATING VIDEOS USING SEQUENCES OF GENERATIVE NEURAL NETWORKS
Simplified Explanation
The patent application describes a method that uses neural networks to generate a video based on a text prompt describing a scene.
Key Features and Innovation
- Utilizes a text encoder neural network to generate a contextual embedding of the text prompt.
- Employs a sequence of generative neural networks to create a final video depicting the scene.
- Integrates text processing and video generation technologies for a seamless user experience.
Potential Applications
This technology can be used in various industries such as entertainment, education, virtual reality, and video production.
Problems Solved
- Streamlines the process of creating videos based on text descriptions.
- Enhances the efficiency and accuracy of video production.
- Provides a novel way to visualize textual content.
Benefits
- Saves time and resources in video production.
- Enables the creation of dynamic and engaging videos.
- Enhances storytelling capabilities through visual representation of text.
Commercial Applications
The technology can be applied in content creation platforms, e-learning systems, marketing campaigns, and virtual reality experiences to enhance user engagement and creativity.
Prior Art
Further research can be conducted in the fields of natural language processing, computer vision, and artificial intelligence to explore similar technologies and advancements in video generation based on text prompts.
Frequently Updated Research
Stay updated on advancements in neural networks, text-to-video technologies, and AI applications in video production to leverage the latest innovations in this field.
Questions about Text-to-Video Technology
How does text encoder neural network enhance video generation based on text prompts?
The text encoder neural network processes the text prompt to generate a contextual embedding, providing a foundation for the subsequent generative neural networks to create a video depicting the scene accurately.
What are the potential applications of text-to-video technology beyond entertainment?
Text-to-video technology can be utilized in education for visualizing complex concepts, in marketing for creating engaging content, and in virtual reality for immersive experiences, among other applications.
Original Abstract Submitted
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium. In one aspect, a method includes receiving a text prompt describing a scene; processing the text prompt using a text encoder neural network to generate a contextual embedding of the text prompt; and processing the contextual embedding using a sequence of generative neural networks to generate a final video depicting the scene.