Model compensations
AssigneeHewlett-Packard Development Company, L.P.
InventorsJuheon LEE, Juan Carlos CATANA SALAZAR, Nathan MORONEY, Jun ZENG
Life of this patent
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Abstract
Examples of methods are described herein. In some examples, a method includes generating, using a compensation machine learning model after training, a compensated model based on a three-dimensional (3D) object model. In some examples, the compensation machine learning model is trained by generating candidate compensation plans and evaluating, using a deformation machine learning model, the candidate compensation plans. In some examples, the method includes adjusting the 3D object model based on the compensated model to produce an adjusted model.
Claims15
A method, comprising:
- generating, using a compensation machine learning model after training, a compensated model based on a three-dimensional (3D) object model, wherein the compensation machine learning model is trained by generating candidate compensation plans and evaluating, using a deformation machine learning model, the candidate compensation plans;
- and
- adjusting the 3D object model based on the compensated model to produce an adjusted model.
An apparatus, comprising:
- a memory;
- a processor in electronic communication with the memory, wherein the processor is to:
- convert a three-dimensional (3D) object model to an isometric mesh;
- predicting, using a compensation machine learning model, compensation of the 3D object model based on the isometric mesh;
- predicting, using a deformation machine learning model, deformation of the 3D object model based on the compensation;
- and
- determining whether the compensation satisfies a condition based on the deformation.
A non-transitory tangible computer-readable medium comprising instructions when executed cause a processor of an electronic device to:
- convert a three-dimensional (3D) object model to an isometric mesh;
- predict, using a first graph neural network, a compensated point cloud indicating compensation to the 3D object model based on a first graph structure of the isometric mesh;
- predict, using a second graph neural network, a deformed point cloud indicating deformation to the compensated point cloud based on a second graph structure of the compensated point cloud;
- and
- adjust the 3D object model based on the deformed point cloud to produce an adjusted 3D object model.
Dependencies are inferred from the claim text.