69 citations · 154 across the 6 of their papers we have counts for
6 papers
GPHM: Gaussian Parametric Head Model for Monocular Head Avatar Reconstruction
Yuelang Xu, Zhaoqi Su, Qingyao Wu +1
Creating high-fidelity 3D human head avatars is crucial for applications in VR/AR, digital human, and film production. Recent advances have leveraged morphable face models to gener…
HHAvatar: Gaussian Head Avatar with Dynamic Hairs
Zhanfeng Liao, Yuelang Xu, Zhe Li +6
Creating high-fidelity 3D head avatars has always been a research hotspot, but it remains a great challenge under lightweight sparse view setups. In this paper, we propose HHAvatar…
High-Fidelity 3D Head Avatars Reconstruction through Spatially-Varying Expression Conditioned Neural Radiance Field
Minghan Qin, Yifan Liu, Yuelang Xu +3
One crucial aspect of 3D head avatar reconstruction lies in the details of facial expressions. Although recent NeRF-based photo-realistic 3D head avatar methods achieve high-qualit…
LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar
Yuelang Xu, Hongwen Zhang, Lizhen Wang +4
Existing approaches to animatable NeRF-based head avatars are either built upon face templates or use the expression coefficients of templates as the driving signal. Despite the pr…
AvatarMAV: Fast 3D Head Avatar Reconstruction Using Motion-Aware Neural Voxels
Yuelang Xu, Lizhen Wang, Xiaochen Zhao +2
With NeRF widely used for facial reenactment, recent methods can recover photo-realistic 3D head avatar from just a monocular video. Unfortunately, the training process of the NeRF…
PIE-NET: Parametric Inference of Point Cloud Edges
Xiaogang Wang, Yuelang Xu, Kai Xu +4
We introduce an end-to-end learnable technique to robustly identify feature edges in 3D point cloud data. We represent these edges as a collection of parametric curves (i.e.,lines,…