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(ACM MM 2025) NaME: A Natural Micro-expression Dataset for Micro-expression Recognition in the Wild

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# NaME: A Natural Micro-expression Dataset for Micro-expression Recognition in the Wild
![License](https://img.shields.io/badge/License-EULA-blue)

# 📊NAME Overview
**NaME** is a **large-scale in-the-wild micro-expression dataset** comprising 506 spontaneous ME samples from 106 multi-cultural participants at 1920×1080 resolution, provided in both face-cropped (background-excluded) and original (background-included) forms. Each sample is annotated by three FACS-certified experts with 24 Action Units, precise temporal markers (onset, apex, offset), and one of six emotion labels: **Happiness 15, Disgust 69, Anger 26, Surprise 162, Sadness 46, and Others 188**.

![image](https://github.com/real-ljt/NAMEdataset/blob/main/samples2_c.png)

## 📥Accessment Request
Please read and fill in the [**End User License Agreement (EULA)**](EULA4NaME.pdf) carefully, then send it to **jiateng_liu@seu.edu.cn**.

## Reference
(MM 2025) NaME: A Natural Micro-expression Dataset for Micro-expression Recognition in the Wild   
[Paper Link](https://dl.acm.org/doi/abs/10.1145/3746027.3755095)   
@inproceedings{liu2025name,  
  title={NaME: A Natural Micro-expression Dataset for Micro-expression Recognition in the Wild},  
  author={Liu, Jiateng and Shi, Hengcan and Liang, Haiwen and Xu, Xiaolin and Zong, Yuan and Wang, Yaonan and Zheng, Wenming},  
  booktitle={Proceedings of the 33rd ACM International Conference on Multimedia},  
  pages={5617--5626},  
  year={2025}}

NAMEdataset

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