Snap inc. (20240355064). OVERLAYING VISUAL CONTENT USING MODEL ADAPTATION simplified abstract

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OVERLAYING VISUAL CONTENT USING MODEL ADAPTATION

Organization Name

snap inc.

Inventor(s)

Daria Skrypnyk of Los Angeles CA (US)

Matthew Hallberg of Los Angeles CA (US)

OVERLAYING VISUAL CONTENT USING MODEL ADAPTATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240355064 titled 'OVERLAYING VISUAL CONTENT USING MODEL ADAPTATION

Simplified Explanation: The system described in the patent application overlays visual content onto a real-world object based on a user's prompt, using a generative machine learning model to populate an image template with visual content representing the user's intent.

  • **Key Features and Innovation:**
   * Identification of user prompts indicating intent
   * Accessing image templates with predefined features
   * Utilizing a generative machine learning model to populate templates
   * Overlaying visual content onto real-world objects based on user intent
  • **Potential Applications:**
   * Augmented reality applications
   * Interactive marketing campaigns
   * Personalized product visualization
  • **Problems Solved:**
   * Enhancing user experience by aligning visual content with user intent
   * Streamlining the process of overlaying digital content onto real-world objects
  • **Benefits:**
   * Improved user engagement
   * Enhanced personalization
   * Efficient content overlay process
  • **Commercial Applications:**
   * "Augmented Reality Content Overlay System for Enhanced User Experience"
  • **Prior Art:**
   Research into similar technologies such as AR content overlay systems and machine learning models for image processing.
  • **Frequently Updated Research:**
   Stay updated on advancements in generative machine learning models and augmented reality technologies.

Questions about AR Content Overlay System: 1. How does the system differentiate between various user prompts to accurately overlay visual content? 

   - The system uses a combination of data associated with the image template and the user's prompt to generate a populated image template.

2. What are the potential challenges in aligning the visual content with the user's intent in real-time applications? 

   - Real-time processing speed and accuracy of the generative machine learning model may pose challenges in accurately overlaying visual content onto real-world objects.


Original Abstract Submitted

described is a system for overlaying visual content onto a real-world object by identifying a prompt of a user indicating a user's intent, accessing an image template, wherein the image template includes placement of features within the image template, and processing a combination of data associated with the image template and the prompt using a generative machine learning model to generate a first populated image template in which one or more portions of the image template are populated with visual content representing the user's intent. the system then proceeds to access an image depicting a real-world object and overlay the first populated image template that includes the visual content representative of the user's intent on at least a portion of the real-world object based on the placement of the features of the image template.

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