Summary of Xhand: Real-time Expressive Hand Avatar, by Qijun Gan and Zijie Zhou and Jianke Zhu
XHand: Real-time Expressive Hand Avatar
by Qijun Gan, Zijie Zhou, Jianke Zhu
First submitted to arxiv on: 30 Jul 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to generating expressive hand avatars for real-time rendering in extended reality and gaming environments is introduced. The proposed XHand model comprehensively generates hand shape, appearance, and deformations by predicting hand deformation displacements, albedo, and linear blending skinning weights using three feature embedding modules. A mesh-based neural renderer leverages mesh topological consistency and latent codes from the embedding modules for photo-realistic rendering on fine-grained meshes. Experimental evaluations demonstrate the efficacy of XHand in recovering high-fidelity geometry and texture for hand animations across diverse poses in real-time. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In this paper, researchers create a new way to make hands look realistic in virtual environments. They made a special kind of computer model called XHand that can change shape, color, and movement in real-time. This is important because it allows people to interact with virtual objects in a more natural way. The scientists used special techniques like embedding modules and mesh-based rendering to make their model work. They tested it on big datasets and showed that it could do things like moving fingers and changing the texture of skin. |
Keywords
» Artificial intelligence » Embedding
