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Tianjian Jiang

7 accepted papers

2024

HSR: Holistic 3D Human-Scene Reconstruction from Monocular Videos

ECCV 2024poster

"An overarching goal for computer-aided perception systems is the holistic understanding of the human-centric 3D world, including faithful reconstructions of humans, scenes, and their global spatial relationships. While recent progress in monocular 3D reconstruction has been made for footage of eith…

Cited by 3SourcePDFScholar
2024

MultiPly: Reconstruction of Multiple People from Monocular Video in the Wild

CVPR 2024poster

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 from monocular in-the-wild videos poses a challenging task. Addressing it necessitates precise pixel-level disentanglemen…

Cited by 9SourcePDFScholar
2024

ReLoo: Reconstructing Humans Dressed in Loose Garments from Monocular Video in the Wild

ECCV 2024poster

"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 exhibit large non-rigid surface deformations during articulation. This limits the application of such methods to humans…

Cited by 7SourcePDFScholar
2023

EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild

ICCV 2023poster

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 with global body and camera trajectories for in-the-wild videos. We use body-worn, wireless electromagnetic (EM) sensors a…

Cited by 52PDFcodeScholar
2023

InstantAvatar: Learning Avatars From Monocular Video in 60 Seconds

CVPR 2023poster

In this paper, we take one step further towards real-world applicability of monocular neural avatar reconstruction by contributing InstantAvatar, a system that can reconstruct human avatars from a monocular video within seconds, and these avatars can be animated and rendered at an interactive rate.…

Cited by 121SourcePDFScholar
2023

Vid2Avatar: 3D Avatar Reconstruction From Videos in the Wild via Self-Supervised Scene Decomposition

CVPR 2023poster

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. Solving it requires accurately separating humans from arbitrary backgrounds. Moreover, it requires reconstructing detail…

2022

gDNA: Towards Generative Detailed Neural Avatars

CVPR 2022poster

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 due to the diversity of clothed body shapes, their complex articulations, and the resulting rich, yet stochastic geomet…

Cited by 84PDFScholar