most citedRecovering Geometric Information with Learned Texture Perturbations

3 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Skinning a Parameterization of Three-Dimensional Space for Neural Network Cloth

Jane Wu, Zhenglin Geng, Hui Zhou +1

We present a novel learning framework for cloth deformation by embedding virtual cloth into a tetrahedral mesh that parametrizes the volumetric region of air surrounding the underl…

cs.LG20201 cited

Imitation Learning for Fashion Style Based on Hierarchical Multimodal Representation

Shizhu Liu, Shanglin Yang, Hui Zhou

Fashion is a complex social phenomenon. People follow fashion styles from demonstrations by experts or fashion icons. However, for machine agent, learning to imitate fashion expert…

cs.CV20203 cited

Recovering Geometric Information with Learned Texture Perturbations

Jane Wu, Yongxu Jin, Zhenglin Geng +2

Regularization is used to avoid overfitting when training a neural network; unfortunately, this reduces the attainable level of detail hindering the ability to capture high-frequen…

cs.CV2019

3D Virtual Garment Modeling from RGB Images

Yi Xu, Shanglin Yang, Wei Sun +3

We present a novel approach that constructs 3D virtual garment models from photos. Unlike previous methods that require photos of a garment on a human model or a mannequin, our app…

cs.CV2019

Pose Guided Fashion Image Synthesis Using Deep Generative Model

Wei Sun, Jawadul H. Bappy, Shanglin Yang +3

Generating a photorealistic image with intended human pose is a promising yet challenging research topic for many applications such as smart photo editing, movie making, virtual tr…