Amazon Technologies, Inc.

Adobe, Inc.

Vidya Narayanan

Sunil Sharadchandra Hadap

Wilmot Wei-Mau Li

Eric Joel Stollnitz

Daniel Max Kaufman

Amanda Paige Ghassaei

Nancy Yi Liang

Michal Lukac

Michal Lukác

Raja Bala

Seungbae Bang

Zoe Rachel Sherman

Yuxuan Mei

An object folding tool is leveraged in a digital medium environment. A two-dimensional (2D) representation of an unfolded object is obtained, and visual cues indicating folds for transforming the unfolded object into a folded object are detected. Based on the detected visual cues, a shape of the folded object is determined, and a three-dimensional (3D) representation of the folded object having the determined shape is generated. In one or more implementations, the 2D representation of the unfolded object and the 3D representation of the folded object are displayed concurrently on a display device.

Object folding tool

Systems and methods are provided for generating a flat garment pattern and/or 3D mesh representation of a garment from one or more images depicting the garment laid flat or hung up. A system may obtain both a front image depicting a front view of a garment and a back image depicting a back view of the garment. A front and back silhouette of the garment may then be generated, which may include segmenting the garment depiction from background image content. A parametric representation of the garment may then be generated based on the front and back silhouettes, which may be implemented by iteratively optimizing, using differentiable rendering techniques, a garment representation within a parametric garment space previously learned for the particular garment type. A 3D mesh garment representation may then be generated based on the parametric representation, from which a flat sewing pattern may subsequently be generated if desired.

Garment pattern generation from image data

Systems and methods are provided for generating custom garment patterns for producing clothing sized to fit any newly input human body representation. A set of reference sample bodies may be selected for which custom designed garment patterns are then obtained. Once reference patterns are obtained, a custom garment pattern for a particular new body may be automatically created by blending two or more of the reference patterns. For example, the neighboring reference bodies to the new body may be identified within a low-dimensional embedding space, and interpolation of garment parameters for the previously designed garment patterns for these reference bodies may be performed to produce a custom garment pattern.

Custom garment pattern blending based on body data

A neighboring panel view is leveraged in a digital medium environment. Initially, a view generation system receives a selection of panels of a three-dimensional (3D) assembled representation of an object, such as to apply digital graphics to the 3D assembled representation. The view generation system also receives a selection of an option to display a neighboring panel view, which is a two-dimensional (2D) flattened view local to the selection. In particular, the neighboring panel view displays an arrangement of the selected panels of the object and their neighboring panels. The view generation system arranges the selected panels in this arrangement as those panels are arranged in the 3D assembled representation. The view generation system also arranges the neighboring panels in the neighboring panel view adjacent to the selected panels with which they are adjacent on the object.

Neighboring panel view

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Pittsburgh, PA, United States of America

Vidya Narayanan