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arXiv cs.GR
arXiv cs.GR Research
· 4 months, 3 weeks ago • Yuxiang Zhao, Wei Huang, Yujie Song, Liu Wang, Huan Zhao

Chatting about Upper-Body Expressive Human Pose and Shape Estimation

Briefing

CoEvoer is designed to improve the estimation of upper-body poses by facilitating feature-level interactions among different body parts. This approach allows for better contextual understanding, where larger regions like the torso inform the estimation of more intricate areas such as the face and hands. Developers in AR/VR should take note of this framework as it promises to enhance realism and user engagement in applications.

With its state-of-the-art performance on upper-body benchmarks and strong generalization capabilities, CoEvoer could redefine how developers approach character animation and interaction in virtual environments. As the demand for expressive avatars grows, integrating such advanced frameworks will be vital for staying competitive in the evolving landscape of game development.

“CoEvoer is the first framework designed specifically for upper-body EHPS.”

— Yuxiang Zhao · Highlighting the novelty of the framework.
What do you think?
How do you see frameworks like CoEvoer changing the way we approach character animation? What challenges have you faced in pose estimation, and how might this framework help?
Start the discussion
Original source
Read on arXiv cs.GR
At a glance
what
Introduction of CoEvoer framework for upper-body EHPS
who
Developed by Yuxiang Zhao and collaborators
when
Submitted on 20 Apr 2026
impact
Enhances accuracy in AR/VR applications, especially for facial and hand regions
Signal Positive

Promising advancements in pose estimation for AR/VR applications.

ar vr pose estimation computer vision
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