Abstract We present Multi-Garment Network (MGN), a method to predict body shape and
clothing, layered on top of the SMPL model from a few frames (1-8) of a video. Several …

Designing and simulating realistic clothing is challenging. Previous methods addressing the
capture of clothing from 3D scans have been limited to single garments and simple motions …

The fashion industry is on the verge of an unprecedented change. The implementation of
machine learning, computer vision, and artificial intelligence (AI) in fashion applications is …

We present Octopus, a learning-based model to infer the personalized 3D shape of people
from a few frames (1-8) of a monocular video in which the person is moving with a …

High-fidelity clothing reconstruction is the key to achieving photorealism in a wide range of
applications including human digitization, virtual try-on, etc. Recent advances in learning …

This article presents a novel approach for 3D mesh labeling by using deep Convolutional
Neural Networks (CNNs). Many previous methods on 3D mesh labeling achieve impressive …

Garment sewing pattern represents the intrinsic rest shape of a garment, and is the core for
many applications like fashion design, virtual try-on, and digital avatars. In this work, we …

In this paper, we present a simple yet effective method to automatically transfer textures of
clothing images (front and back) to 3D garments worn on top SMPL, in real time. We first …

Apparel's significant role in human appearance underscores the importance of garment
digitalization for digital human creation. Recent advances in 3D content creation are pivotal …