Text-Guided Reference Image Generation for 3D View Editing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional three-dimensional modeling applications require manual navigation and advanced technical skills for obtaining desired views and editing digital environments, which are time-consuming and inefficient.
Innovation Solution
A processing device generates reference digital images based on semantic properties of text-based inputs and perceptual similarity to the three-dimensional environment, allowing for efficient navigation and editing using techniques like CLIP models and depth-conditioned image generation neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual navigation is used in three-dimensional modeling applications, then users can obtain desired views, but the process is time-consuming and computationally inefficient
Solution Approach 1:
The patent replaces manual mechanical navigation operations with an automated image generation system that uses CLIP models and neural networks to automatically generate reference images from text descriptions, eliminating the need for manual navigation through three-dimensional space
Solution Approach 2:
The system enables self-service by allowing users to generate desired views simply by providing text descriptions, with the automated system handling the complex navigation and image generation processes without requiring user expertise in three-dimensional modeling operations
2Adaptability or versatility
If manual navigation is used to obtain desired views, then users can explore the digital environment, but the process is computationally inefficient
Solution Approach 1:
The patent replaces computationally intensive manual navigation operations with an optimized automated system that generates reference images through trained neural networks, significantly reducing computational overhead while maintaining view exploration capabilities
3Manufacturing precision
If advanced technical skills are required for editing digital environments, then precise control is achieved, but the system becomes difficult to operate for general users
Solution Approach 1:
The patent introduces text-based descriptions as an intermediary between user intent and complex editing operations, allowing users to specify desired edits through natural language rather than requiring knowledge of complex modeling parameters or operations
Solution Approach 2:
The system replaces complex manual editing operations with automated image generation and manipulation processes that interpret text descriptions and apply appropriate transformations, maintaining precision while eliminating the need for advanced technical skills
Data Source
AI summary
Techniques for text-based reference image generation are described that support generation of reference digital images of a three-dimensional representation of a digital environment. In an example, a processing device receives a text-based input that describes a feature of a three-dimensional representation of a digital environment. The processing device generates a reference digital image for output that depicts a view of the feature based on a perceptual similarity between the reference digital image and semantic properties of the text-based input. The processing device is further operable to apply one or more edits to the reference digital image based on features of the digital environment as well as on additional user inputs.