View Consistent Texture Generation for 3D Objects
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Solution Overview
Problem
The process of creating view-consistent textures for three-dimensional (3D) objects in computer graphics is time-consuming and arduous, especially when ensuring that the stylized mesh aligns seamlessly with global styles or environments.
Innovation Solution
A computer-implemented method using a generative machine-learning (genML) model to generate view-consistent textures for 3D objects. This involves generating depth maps based on the 3D mesh, receiving a texture description from a user, and using the genML model to create multiple views of a texture map, which are then combined to produce a consistent texture map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual texture creation processes are used, then texture quality and style consistency can be controlled, but the time required for texture creation increases significantly
Solution Approach 1:
The patent replaces manual texture creation processes with an automated machine learning-based system. The genML model automatically generates texture maps from 3D meshes based on text prompts, eliminating the need for manual artists to create textures from scratch. This substitution of mechanical (manual) work with automated intelligent systems directly addresses the time loss and productivity issues.
Solution Approach 2:
The system enables self-service texture generation where the genML model autonomously creates textures without requiring professional artists. The automated pipeline processes 3D meshes and generates appropriate texture maps independently, allowing users to obtain high-quality textures through simple text descriptions without manual intervention in the texture creation process.
2Productivity
If automated texture generation is used, then texture creation speed increases, but ensuring view-consistency and style alignment becomes more difficult
Solution Approach 1:
The patent implements feedback mechanisms where the system generates multiple texture views and uses this information to refine and adjust subsequent generations. The process iteratively improves texture consistency by comparing generated views against each other and against the original 3D mesh, allowing the system to correct inconsistencies and maintain style alignment automatically.
Solution Approach 2:
The system performs preliminary actions by generating multiple texture views in advance before final assembly. By pre-generating consistent textures for different viewpoints and storing them as reference material, the system ensures that when textures are applied to the 3D mesh, view-consistency is maintained. This preliminary generation of multiple views prevents inconsistency issues from arising during the final rendering process.
3Manufacturing precision
If multiple texture views are generated, then view-consistency improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent segments the texture generation process into separate views or regions. Instead of generating one complex texture map, the system divides the 3D object into multiple viewpoints and generates textures for each view separately using the genML model. This segmentation allows the system to maintain view-consistency by ensuring each view is generated independently and then assembled, reducing the computational complexity of generating a single comprehensive texture.
Solution Approach 2:
The system transitions from two-dimensional texture maps to three-dimensional view-based generation. By generating textures for multiple viewpoints (front, back, sides) and using depth information to guide the generation process, the system adds a dimensional aspect that enables better view-consistency. This 3D-aware approach allows the genML model to understand spatial relationships and generate consistent textures across different perspectives without requiring excessive computational resources for a single monolithic texture generation task.
Data Source
AI summary
Various implementations relate to methods, systems, and computer-readable media to generate view consistent textures for three-dimensional (3D) objects. In some implementations, a method includes generating a plurality of depth maps based on a 3D mesh of a 3D object, wherein each of the plurality of depth maps is associated with a respective view of the 3D object. The method further includes receiving a description of a texture and generating two or more views of a texture map for the 3D object with a generative machine-learning (genML) model. The plurality of depth maps and a text prompt based on the description are provided as input to the genML model. Each view of the texture map at least partially covers the 3D mesh. The method further includes combining the two or more views of the texture map based on the 3D mesh to obtain the texture map for the 3D object.