65 citations · 252 across the 21 of their papers we have counts for
6 papers · 1 filter
HairLRM: Strand-based Hair Modeling via Large Reconstruction Models
Yuefan Shen, Yican Dong, Xiufeng Huang +3
The fundamental limitation of traditional strand-based modeling is not simply data scarcity, but the ill-posedness of inferring complex 3D fields from 2D imagery without structural…
NeuralHDHair: Automatic High-fidelity Hair Modeling from a Single Image Using Implicit Neural Representations
Keyu Wu, Yifan Ye, Lingchen Yang +3
Undoubtedly, high-fidelity 3D hair plays an indispensable role in digital humans. However, existing monocular hair modeling methods are either tricky to deploy in digital systems (…
GCN-Denoiser: Mesh Denoising with Graph Convolutional Networks
Yuefan Shen, Hongbo Fu, Zhongshuo Du +5
In this paper, we present GCN-Denoiser, a novel feature-preserving mesh denoising method based on graph convolutional networks (GCNs). Unlike previous learning-based mesh denoising…
DeepSketchHair: Deep Sketch-based 3D Hair Modeling
Yuefan Shen, Changgeng Zhang, Hongbo Fu +2
We present sketchhair, a deep learning based tool for interactive modeling of 3D hair from 2D sketches. Given a 3D bust model as reference, our sketching system takes as input a us…
Hair-GANs: Recovering 3D Hair Structure from a Single Image
Meng Zhang, Youyi Zheng
We introduce Hair-GANs, an architecture of generative adversarial networks, to recover the 3D hair structure from a single image. The goal of our networks is to build a parametric…
Ergonomic-driven Geometric Exploration and Reshaping
Youyi Zheng, Julie Dorsey, Niloy Mitra
The paper addresses the following problem: given a set of man-made shapes, e.g., chairs, can we quickly rank and explore the set of shapes with respect to a given avatar pose? Answ…