Human-Centric-AI
Human-Centric AI Resources
An open, community-driven hub for human-centric AI.
Human-Centric AI Resources is an open and evolving hub that brings together academic knowledge, research infrastructure, community learning materials, and curated literature across human-centric AI. The accompanying survey provides a structured perspective through its six-level human context taxonomy, while this repository extends beyond the survey to support broader resource discovery and community curation.
[!TIP] Join the community. We welcome everyone interested in human-centric AI to help maintain and enrich this open resource hub. If you are interested in getting involved, feel free to contact us using the details at the bottom of this page.
📢 News
- 2026-09-06: Our work was featured by 机器之心: 从「看见人」到「行动如人」：基础模型时代的Human-Centric AI全谱系综述.
- 2026-08-10: Our project homepage is now live.
- 2026-08-08: First resource release.
🧭 Start Here
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Discover Research Explore curated research through our survey taxonomy and complementary community collections. |
Build Human-Centric Systems Access reusable infrastructure for developing and evaluating human-centric AI systems. |
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Learn the Field Build a structured understanding of the field through open academic learning materials. |
Follow the Community Stay connected with the research community and its evolving knowledge ecosystem. |
🧩 Human Context Spectrum
The collection follows six connected contexts, progressing from observable human properties to interaction, world evolution, and executable agency.
 Visual Appearance |
 Spatial Geometry |
 Kinematic Dynamics |
 Interaction Modeling |
 World Simulation |
 Embodied Agency |
✍️ Citation
If this resource collection is useful in your research, please cite the accompanying survey:
@article{chen2026humancentricAI,
title={Human-Centric Intelligence in the Era of Foundation Models: A Survey},
author={Chen, Yang and Wang, Tianqi and Jiang, Xiaorui and Man, Yilei and Shao, Yihua and Liu, Mengyuan and Chen, Zhi and Cao, Xiaofeng and Zhao, Qibin and Liu, Chi Harold and Zomaya, Albert Y and Sebe, Nicu and Zhou, Jingren and Tao, Dacheng and Guo, Song and Guo, Jingcai},
journal={arXiv preprint arXiv:2608.18184},
year={2026}
}
📧 Contact
For questions, suggestions, or collaboration inquiries, please contact the project lead, Yang Chen:
- Email: cs-yang.chen@connect.polyu.hk
- WeChat:
cs-yangchen(please include your name, institutional affiliation, and reason for contacting in the friend request)
📜 License
Source code is licensed under the MIT License. Original documentation, curated resource metadata, and the authorized survey figures are licensed under CC BY 4.0. Logos, unlisted visual assets, and third-party materials may be subject to separate terms. See LICENSE and Third-Party Notices for the complete scope.
If this project helps you, please give it a Star.
Curated and maintained by Lumen Lab @ The Hong Kong Polytechnic University