16 citations · 19 across the 8 of their papers we have counts for
8 papers
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…
AvatarPose: Avatar-guided 3D Pose Estimation of Close Human Interaction from Sparse Multi-view Videos
Feichi Lu, Zijian Dong, Jie Song +1
Despite progress in human motion capture, existing multi-view methods often face challenges in estimating the 3D pose and shape of multiple closely interacting people. This difficu…
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…
4D-DRESS: A 4D Dataset of Real-world Human Clothing with Semantic Annotations
Wenbo Wang, Hsuan-I Ho, Chen Guo +5
The studies of human clothing for digital avatars have predominantly relied on synthetic datasets. While easy to collect, synthetic data often fall short in realism and fail to cap…
GraspXL: Generating Grasping Motions for Diverse Objects at Scale
Hui Zhang, Sammy Christen, Zicong Fan +2
Human hands possess the dexterity to interact with diverse objects such as grasping specific parts of the objects and/or approaching them from desired directions. More importantly,…
SiTH: Single-view Textured Human Reconstruction with Image-Conditioned Diffusion
Hsuan-I Ho, Jie Song, Otmar Hilliges
A long-standing goal of 3D human reconstruction is to create lifelike and fully detailed 3D humans from single-view images. The main challenge lies in inferring unknown body shapes…
SynH2R: Synthesizing Hand-Object Motions for Learning Human-to-Robot Handovers
Sammy Christen, Lan Feng, Wei Yang +3
Vision-based human-to-robot handover is an important and challenging task in human-robot interaction. Recent work has attempted to train robot policies by interacting with dynamic…
ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulation
Hui Zhang, Sammy Christen, Zicong Fan +4
We present ArtiGrasp, a novel method to synthesize bi-manual hand-object interactions that include grasping and articulation. This task is challenging due to the diversity of the g…