Search Results for author: Mengcheng Li

Found 6 papers, 2 papers with code

HHMR: Holistic Hand Mesh Recovery by Enhancing the Multimodal Controllability of Graph Diffusion Models

no code implementations CVPR 2024 Mengcheng Li, Hongwen Zhang, Yuxiang Zhang, Ruizhi Shao, Tao Yu, Yebin Liu

In this paper, we extend the ability of controllable generative models for a more comprehensive hand mesh recovery task: direct hand mesh generation, inpainting, reconstruction, and fitting in a single framework, which we name as Holistic Hand Mesh Recovery (HHMR).

3D Hand Pose Estimation Gesture Recognition

4DHands: Reconstructing Interactive Hands in 4D with Transformers

no code implementations30 May 2024 Dixuan Lin, Yuxiang Zhang, Mengcheng Li, Yebin Liu, Wei Jing, Qi Yan, Qianying Wang, Hongwen Zhang

The results on in-the-wild videos and real-world scenarios demonstrate the superior performances of our approach for interactive hand reconstruction.

Learning Explicit Contact for Implicit Reconstruction of Hand-held Objects from Monocular Images

no code implementations31 May 2023 Junxing Hu, Hongwen Zhang, Zerui Chen, Mengcheng Li, Yunlong Wang, Yebin Liu, Zhenan Sun

In the second part, we introduce a novel method to diffuse estimated contact states from the hand mesh surface to nearby 3D space and leverage diffused contact probabilities to construct the implicit neural representation for the manipulated object.

Object

PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images

1 code implementation13 Jul 2022 Hongwen Zhang, Yating Tian, Yuxiang Zhang, Mengcheng Li, Liang An, Zhenan Sun, Yebin Liu

To address these issues, we propose a Pyramidal Mesh Alignment Feedback (PyMAF) loop in our regression network for well-aligned human mesh recovery and extend it as PyMAF-X for the recovery of expressive full-body models.

Ranked #6 on 3D Human Pose Estimation on AGORA (using extra training data)

3D human pose and shape estimation Human Mesh Recovery +2

Lightweight Multi-person Total Motion Capture Using Sparse Multi-view Cameras

no code implementations ICCV 2021 Yuxiang Zhang, Zhe Li, Liang An, Mengcheng Li, Tao Yu, Yebin Liu

Overall, we propose the first light-weight total capture system and achieves fast, robust and accurate multi-person total motion capture performance.

3D Multi-Person Pose Estimation

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