most citedSynH2R: Synthesizing Hand-Object Motions for Learning Human-to-Robot Handovers

16 citations · 19 across the 8 of their papers we have counts for

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cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2023

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…