18746911. CONTEXT-AWARE SYNTHESIS AND PLACEMENT OF OBJECT INSTANCES simplified abstract (NVIDIA Corporation)
Contents
CONTEXT-AWARE SYNTHESIS AND PLACEMENT OF OBJECT INSTANCES
Organization Name
Inventor(s)
Donghoom Lee of Sunnyvale CA (US)
Sifei Liu of Santa Clara CA (US)
Ming-Yu Liu of San Jose CA (US)
Jan Kautz of Lexington MA (US)
CONTEXT-AWARE SYNTHESIS AND PLACEMENT OF OBJECT INSTANCES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18746911 titled 'CONTEXT-AWARE SYNTHESIS AND PLACEMENT OF OBJECT INSTANCES
The abstract of this patent application describes a method that involves using generator models to manipulate images and insert objects into them based on semantic representations.
- Applying a first generator model to a semantic representation of an image to generate an affine transformation representing a bounding box of a region within the image.
- Applying a second generator model to the affine transformation and semantic representation to generate the shape of an object.
- Inserting the object into the image based on the bounding box and shape.
Potential Applications: - Image editing software - Augmented reality applications - Virtual reality environments
Problems Solved: - Efficiently inserting objects into images - Enhancing the realism of augmented reality experiences
Benefits: - Improved accuracy in object placement - Streamlined image editing processes - Enhanced visual effects in virtual and augmented reality
Commercial Applications: Title: Advanced Image Editing Technology for Augmented Reality Applications This technology can be used in the development of advanced image editing software for professionals in the fields of graphic design, advertising, and entertainment. It can also be integrated into augmented reality applications for enhanced user experiences.
Questions about the technology: 1. How does this technology improve the accuracy of object insertion in images? 2. What are the potential limitations of using generator models for image manipulation and object insertion?
Original Abstract Submitted
One embodiment of a method includes applying a first generator model to a semantic representation of an image to generate an affine transformation, where the affine transformation represents a bounding box associated with at least one region within the image. The method further includes applying a second generator model to the affine transformation and the semantic representation to generate a shape of an object. The method further includes inserting the object into the image based on the bounding box and the shape.
