Abstract: Provided is a method for 3D modeling based on an irregular-shaped sketch, in which the method is executed by one or more processors, and includes receiving 2D sketch data of a target object, inputting the 2D sketch data into a 3D model generation model to generate a 3D model of the target object, and displaying the generated 3D model on a display.

Abstract: Provided is a method for generating a freehand sketch of a 3D model for machine learning, which is executed by one or more processors, in which a method for generating freehand sketch data for machine learning includes receiving a 3D model of a target object, and generating a plurality of different freehand sketch images for the target object based on the 3D model.

Abstract: Provided is a method for 3D modeling based on an irregular-shaped sketch, in which the method is executed by one or more processors, and includes receiving 2D sketch data of a target object, inputting the 2D sketch data into a 3D model generation model to generate a 3D model of the target object, and displaying the generated 3D model on a display.

Abstract: Provided is a method for generating a freehand sketch of a 3D model for machine learning, which is executed by one or more processors, in which a method for generating freehand sketch data for machine learning includes receiving a 3D model of a target object, and generating a plurality of different freehand sketch images for the target object based on the 3D model.

Abstract: A method for providing an XR object is provided, which is executed by one or more processors, and includes receiving a plurality of images obtained by capturing an image of a target object positioned in a specific space from different directions, generating an XR object for the target object based on the plurality of images, generating a code for applying the XR object to an online platform, and transmitting the code to a first user terminal.

Abstract: The present disclosure relates to a method for 3D modeling based on volume estimation, in which the method is executed by one or more processors, and includes receiving a plurality of images obtained by capturing an image of a target object positioned in a specific space from different directions, estimating a position and pose at which each image is captured, training a volume estimation model based on the plurality of images and the position and pose at which each image is captured, and generating a 3D model of the target object by using the volume estimation model.