A computer implemented method simulates a flexible material. The method includes representing the flexible material with a mesh that includes bilinear quadrilateral mesh elements with a specified number of degrees of freedom per vertex. The method also includes computing a per-element deformation strain value for the mesh elements, wherein deformation strain values depend on a second order function with respect to the degrees of freedom of the vertices of the mesh elements. The method also includes simulating motion of the flexible material using the deformation strains of each mesh element to simulate motion of the vertices along the specified number degrees of freedom.

The invention relates to three computer implemented methods providing virtual fitting room functionality to a human. The three computer implemented methods allow for a simple and efficient garment selection process by the human.

A method for flattening a three-dimensional shoe upper template is provided. The method includes providing a three-dimensional last model, obtaining a three-dimensional grid model, obtaining a three-dimensional thickened grid model, obtaining a two-dimensional initial-value grid model, and obtaining a two-dimensional grid model with the smallest energy value. A system and a non-transitory computer-readable medium for performing the method are also provided. The method makes it possible to precisely flatten a three-dimensional last model with a non-developable surface and thereby convert the three-dimensional last model into a two-dimensional grid model.

This disclosure relates generally to method and system for draping a 3D garment on a 3D human body. Dressing digital humans in 3D have gained much attention due to its use in online shopping and draping 3D garments over the 3D human body has immense applications in virtual try-on, animations, and accurate fitment of the 3D garment is the utmost importance. The proposed disclosure is a single unified garment deformation model that learns the shared space of variations for a body shape, a body pose, and a styling garment. The method receives a plurality of human body inputs to construct a 3D skinned garments for the subject. The deep draper network trained using a plurality of losses provides efficient deep neural network based method that predicts fast and accurate 3D garment images. The method couples the geometric and multi-view perceptual constraints that efficiently learn the garment deformation's high-frequency geometry.

First image data representing a first human wearing a first article of clothing may be received. The first image data, when rendered on a display, may include a first photometric artifact. A first generator network may be used to generate second image data from the first image data. The first photometric artifact may be removed from the second image data. A second generator network may be used to generate third image data from the second image data, the third image data representing the first human in a different pose relative to the first image data. Fourth image data representing the first article of clothing segmented from the first human may be generated and displayed on a display.

Disclosed are computer-readable devices, systems and methods for generating a model of a clothed body. The method includes generating a model of an unclothed human body, the model capturing a shape or a pose of the unclothed human body, determining two-dimensional contours associated with the model, and computing deformations by aligning a contour of a clothed human body with a contour of the unclothed human body. Based on the two-dimensional contours and the deformations, the method includes generating a first two-dimensional model of the unclothed human body, the first two-dimensional model factoring the deformations of the unclothed human body into one or more of a shape variation component, a viewpoint change, and a pose variation and learning an eigen-clothing model using principal component analysis applied to the deformations, wherein the eigen-clothing model classifies different types of clothing, to yield a second two-dimensional model of a clothed human body.

A method and system for generating user driven adaptive object visualizations using Generative Adversarial Network (GAN) models is disclosed. The method includes the steps of generating a first set of object vectors for an object based on at least one input received from a user. The first set of vectors corresponds to a first set of visualizations for the object The method further includes capturing at least one tacit reaction type of the user in response to user interaction with each of the first set of visualizations, computing a score for each portion of each of the first set of visualizations, identifying a plurality of portions from at least one of the first set of object visualizations, generating a second set of object vectors, and processing the second set of object vectors sequentially through a plurality of GAN models to generate a final object visualization of the object.

Provided is method and system for organizing a virtual showroom with one or more 3d images. Scripts are generated from the input images provided by the user, for generating 3D images of the products in the showroom. The generated 3D images can be in folded form, hanger display or mannequin.

In various example embodiments, a system and method for modifying publications of a network-based publication system are presented. The system receives a set of body coordinates from a client device and associates the set of body coordinates with a user account. The system identifies a set of clothing images within a set of publications retrieved as a result of a query. The system generates a set of modified clothing images from one or more images of the set of clothing images and causes presentation of the set of modified clothing images at the client device.

A method and apparatus for simulating clothes receive a user setting for an area in which shirring is to be expressed in a two-dimensional (2D) pattern of clothes modeled with a mesh including a plurality of polygons, obtain a first line and a second line parallel to the first line from the area based on the user setting, generate inner lines that are perpendicular to at least one of the first line and the second line of the area between the first line and the second line and that have regular intervals, align polygons included in the area of the 2D pattern based on the inner lines, and perform a draping simulation of three-dimensional (3D) clothes corresponding to the 2D pattern in which the shirring is expressed by the aligned polygons.