H4MER: Human 4D Modeling by Learning Neural Compositional Representation With Transformer-Reference-Cited by-同舟云学术

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H4MER: Human 4D Modeling by Learning Neural Compositional Representation With Transformer

Published:2023-12 Issue:12 Volume:45 Page:14639-14652
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Jiang Boyan¹^ORCID,Zhang Yinda²^ORCID,Huo Jingyang³^ORCID,Xue Xiangyang¹^ORCID,Fu Yanwei⁴^ORCID

Affiliation:

1. School of Computer Science, Fudan University, Shanghai, China

2. Google, Mountain View, CA, USA

3. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

4. School of Data Science and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10308548/10246392.pdf?arnumber=10246392

Reference90 articles.

1. Unite the People: Closing the Loop Between 3D and 2D Human Representations

2. HoloPose: Holistic 3D Human Reconstruction In-The-Wild

3. Single-Shot Multi-person 3D Pose Estimation from Monocular RGB

4. Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image

5. Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the Loop

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