Snap inc. (20240249474). IMAGE GENERATION FROM TEXT AND 3D OBJECT simplified abstract
Contents
IMAGE GENERATION FROM TEXT AND 3D OBJECT
Organization Name
Inventor(s)
Avihay Assouline of Tel Aviv (IL)
Itamar Berger of Hod Hasharon (IL)
Gal Dudovitch of Tel Aviv (IL)
IMAGE GENERATION FROM TEXT AND 3D OBJECT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240249474 titled 'IMAGE GENERATION FROM TEXT AND 3D OBJECT
- Simplified Explanation:**
The patent application describes a system that generates images of real-world objects in scenes by combining a depth map, a 3D model of the object, and a textual description for the background using a machine learning model.
- Key Features and Innovation:**
- System generates images depicting real-world objects in scenes
- Utilizes depth map, 3D model, and textual description for background
- Machine learning model used to combine image content and textual description
- Potential Applications:**
This technology could be used in various industries such as:
- Entertainment (creating realistic scenes for movies or video games)
- Interior design (visualizing furniture in a room)
- E-commerce (showcasing products in different environments)
- Problems Solved:**
- Simplifies the process of generating images with real-world objects in scenes
- Enhances visual representation of objects in different backgrounds
- Improves efficiency in creating realistic visual content
- Benefits:**
- Saves time and resources in image generation
- Enhances visual storytelling and product showcasing
- Increases the realism and accuracy of scene images
- Commercial Applications:**
- "Advanced Image Generation System for Realistic Scene Depiction"
- Potential commercial uses include advertising, virtual staging, and digital content creation
- Market implications include improved visual marketing strategies and enhanced customer engagement
- Questions about Image Generation System:**
1. How does the system ensure accuracy in combining the depth map, 3D model, and textual description? 2. What are the limitations of the machine learning model in generating scene images with real-world objects?
Original Abstract Submitted
aspects of the present disclosure involve a system for generating images that depict a real-world object in a scene. the system receives image content comprising a depth map of a scene and a three-dimensional (3d) model of a real-world object. the system receives a textual description for a background. the system applies the image content and the textual description to a machine learning model to generate a scene image that depicts the real-world object on the background corresponding to the textual description.
