AI 2D-to-3D Asset Generation With Automated Image Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Online retailers face challenges in providing customers with 3D representations of products, as generating 3D assets typically requires manual effort by skilled artists, limiting scalability and efficiency.
Innovation Solution
An automated 3D asset generation framework using AI pipelines processes 2D images to create 3D assets, employing deep convolutional neural networks, image segmentation, and super-resolution models to enhance and validate image quality, enabling efficient and accurate conversion of 2D images into 3D models for virtual environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual creation by experienced 3D artists is used, then high-quality 3D assets are produced, but productivity is low and costs are high
Solution Approach 1:
The patent replaces manual mechanical 3D modeling work with an automated AI-based system that uses computer vision and machine learning algorithms to generate 3D assets from 2D images, eliminating the need for manual artist intervention while maintaining quality standards
Solution Approach 2:
The system creates accurate 3D copies of physical products by capturing 2D images and using AI algorithms to reconstruct three-dimensional models, enabling digital representations that faithfully replicate the original objects without manual modeling
2Manufacturing precision
If manual creation by experienced 3D artists is used, then high-quality 3D assets are produced, but the process is not scalable
Solution Approach 1:
The patent replaces manual mechanical 3D modeling work with an automated AI-based system that uses computer vision and machine learning algorithms to generate 3D assets from 2D images, eliminating the need for manual artist intervention while maintaining quality standards
Solution Approach 2:
The system is designed to handle multiple types of products and 2D image formats through a universal AI pipeline that can process various inputs and generate corresponding 3D assets across different categories, enabling scalable application across diverse product lines
3Productivity
If automated AI pipelines are used, then productivity and scalability are improved, but image processing complexity increases
Solution Approach 1:
The patent divides the complex image processing task into distinct sequential stages including image input, 3D model generation, and validation phases, with each stage handled by specialized AI components that process specific aspects of the transformation independently
Solution Approach 2:
The system introduces intermediate processing steps and validation layers that mediate between the input 2D images and final 3D outputs, using AI models to bridge the transformation while maintaining quality control and reducing overall system complexity through modular architecture
Data Source
AI summary
A system including a processor and a non-transitory computer-readable media storing computing instructions that, when executed on the processor, cause the processor to perform certain operations. The operations can include identifying a 2D silo image of a geometric item based on a probability value exceeding a predetermined probability threshold. The operations also can include segmenting artifacts from the 2D silo image to isolate first pixels of a border of the geometric item. The operations further can include trimming second pixels along the border of the geometric item. The operations also can include performing an aspect ratio validation on the 2D silo image to validate that the 2D silo image corresponds to a shape of the geometric item. The operations additionally can include auto-validating that a visual resolution level of the 2D silo image falls within a predetermined acceptance rate. The operations further can include generating a 3D view image from the 2D silo image of the geometric item enabled for use in virtual environments when the visual resolution level falls within the predetermined acceptance rate. Other embodiments are described.