4 citations · 14 across the 8 of their papers we have counts for
9 papers
Gaussian Wardrobe: Compositional 3D Gaussian Avatars for Free-Form Virtual Try-On
Zhiyi Chen, Hsuan-I Ho, Tianjian Jiang +3
We introduce Gaussian Wardrobe, a novel framework to digitalize compositional 3D neural avatars from multi-view videos. Existing methods for 3D neural avatars typically treat the h…
WorldPose: A World Cup Dataset for Global 3D Human Pose Estimation
Tianjian Jiang, Johsan Billingham, Sebastian Müksch +7
We present WorldPose, a novel dataset for advancing research in multi-person global pose estimation in the wild, featuring footage from the 2022 FIFA World Cup. While previous data…
ReLoo: Reconstructing Humans Dressed in Loose Garments from Monocular Video in the Wild
Chen Guo, Tianjian Jiang, Manuel Kaufmann +4
While previous years have seen great progress in the 3D reconstruction of humans from monocular videos, few of the state-of-the-art methods are able to handle loose garments that e…
MultiPly: Reconstruction of Multiple People from Monocular Video in the Wild
Zeren Jiang, Chen Guo, Manuel Kaufmann +4
We present MultiPly, a novel framework to reconstruct multiple people in 3D from monocular in-the-wild videos. Reconstructing multiple individuals moving and interacting naturally…
EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild
Manuel Kaufmann, Jie Song, Chen Guo +5
We present EMDB, the Electromagnetic Database of Global 3D Human Pose and Shape in the Wild. EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters wi…
Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition
Chen Guo, Tianjian Jiang, Xu Chen +2
We present Vid2Avatar, a method to learn human avatars from monocular in-the-wild videos. Reconstructing humans that move naturally from monocular in-the-wild videos is difficult.…
InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds
Tianjian Jiang, Xu Chen, Jie Song +1
In this paper, we take a significant step towards real-world applicability of monocular neural avatar reconstruction by contributing InstantAvatar, a system that can reconstruct hu…
Fast-SNARF: A Fast Deformer for Articulated Neural Fields
Xu Chen, Tianjian Jiang, Jie Song +4
Neural fields have revolutionized the area of 3D reconstruction and novel view synthesis of rigid scenes. A key challenge in making such methods applicable to articulated objects,…
gDNA: Towards Generative Detailed Neural Avatars
Xu Chen, Tianjian Jiang, Jie Song +4
To make 3D human avatars widely available, we must be able to generate a variety of 3D virtual humans with varied identities and shapes in arbitrary poses. This task is challenging…