Semantic segmentation method, device and equipment and computer readable storage medium

Abstract

The invention provides a semantic segmentation method, device and equipment and a computer readable storage medium. The method comprises the steps: obtaining a display operation for a three-dimensional model; in response to the display operation, displaying the three-dimensional model on a human-computer interaction interface, wherein the human-computer interaction interface comprises semantic segmentation options; obtaining a selection operation for the semantic segmentation options; and in response to the selection operation, after a two-dimensional segmentation result of a two-dimensional image is obtained, displaying a semantic segmentation result of the three-dimensional model on the human-computer interaction interface, wherein the semantic segmentation result is determined accordingto the two-dimensional segmentation result of the two-dimensional image and the model attribute of the three-dimensional model, and the two-dimensional image and the three-dimensional model belong tothe same scene. Through the semantic segmentation method based on artificial intelligence provided by the invention, the segmentation efficiency of the three-dimensional model can be improved, and the user experience is improved.

Description

technical field [0001] The present application relates to data processing technology, and in particular to a semantic segmentation method, device, equipment and computer-readable storage medium. Background technique [0002] Artificial Intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. Among them, 3D object reconstruction (3D object reconstruction) and target segmentation (Target segmentation) are important branches of artificial intelligence. In practical engineering applications, it is necessary to perform semantic segmentation on a specific 3D model to obtain a partial 3D model of the target object. Carry out subsequent engineering applications. [0003] In the traditional 3D model segmentation process, the point cloud data of the 3D model ...

AI Technical Summary

Problems solved by technology

[0003] In the traditional 3D model segmentation process, the point cloud data of the 3D model is often semantically segmented according to the 3D segmentation network. Due to the huge amount of point cloud data, in the actual segmentation process, not only the amount of calculation is large, but also time-consuming , and the segmentation accuracy is low, it is impossible to get a more realistic semantic segmentation result

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