Abstract: The present disclosure relates to method and apparatus for removing shadows from a High Resolution (HR) image. The HR image including shadows is received. The HR image converted into Low Resolution (LR) image. LR shadow-free image is generated from the LR image using first Artificial Intelligence (AI) model. A HR shadow-free image is generated based on combination of the LR shadow-free image and the HR image using second AI model. The present disclosure provides an efficient framework and lightweight network architectures which are used to remove the shadows based on corresponding shadow characteristics. The framework can be deployed in resource-constrained platforms. The present disclosure facilitates processing selected areas of the HR image and retaining the unselected area. Thus, less computational resources are required.

Abstract: An electronic device according to an embodiment disclosed herein may include a communication circuit, a processor; and a memory configured to be operatively connected to the processor. The memory according to an embodiment may store instructions that, when executed, cause the processor to: recognize an area comprising at least part of a face in an image to be transmitted to an external device; generate perturbation data about the recognized area based on a machine learning model stored in the memory; apply the perturbation data to the recognized area; and transmit the image to which the perturbation data has been applied to the external device. Various other embodiments are possible.

Abstract: Provided is a new method which creates the virtual garment from a single photograph of a real garment put on to the mannequin. The method uses the pattern drafting theory in the clothing field. The drafting process is abstracted into a computer module, which takes the garment type and primary body sizes then produces the draft as the output. Then the problem is reduced to find out the garment type and primary body sizes. That information is found by analyzing the silhouette of the garment with respect to the mannequin. The method works robustly and produces practically usable virtual clothes that can be used for the graphical coordination.

Abstract: An automatic garment grading is provided. A retargeting technique is used with the mediator and the correspondence function. The mediator is a parameterized draft. Local coordinates systems are used for making correspondence. The mean value coordinates system (MVC) are improved so that the weights would have positive values, which is omitted mean value coordinates (OMVC). The mediator is parameterized draft, and correspondence function is the OMVC in the method. Smart grading can minimize designer's specialized know-how and save performing time for the grading of real garment and virtual garment.

Abstract: An automatic garment grading is provided. A retargeting technique is used with the mediator and the correspondence function. The mediator is a parameterized draft. Local coordinates systems are used for making correspondence. The mean value coordinates system (MVC) are improved so that the weights would have positive values, which is omitted mean value coordinates (OMVC). The mediator is parameterized draft, and correspondence function is the OMVC in the method. Smart grading is less time-consuming and easy to implement, and can minimize designer's specialized know-how and save performing time for the grading of real garment and virtual garment.