├── README.md └── illu_AAF.png /README.md: -------------------------------------------------------------------------------- 1 | # All-Age-Faces Dataset 2 | ![Alt Text](https://github.com/JingchunCheng/All-Age-Faces-Dataset/blob/master/illu_AAF.png) 3 | 4 | Download link (baidu): https://pan.baidu.com/s/1WtHQsb73rLa-cZpBLi2dtg
5 | Download link (dropbox): https://www.dropbox.com/s/a0lj1ddd54ns8qy/All-Age-Faces%20Dataset.zip?dl=0 6 | 7 | Contact: Jingchun Cheng (chengjingchun at gmail dot com) 8 | 9 | 10 | The All-Age-Faces (AAF) Dataset contains 13'322 face images (mostly Asian) distributed across all ages (from 2 to 80), including 7381 females and 5941 males. 11 | 12 | The orignal face images, facial landmarks and aligned face images are stored in folder `original images`, `key points`, and `aligned faces`, respectively. 13 | We show an example of landmark distribution in folder `example`. 14 | 15 | Each image contains a different individual, and is given a unique name (`%05dA%02d.jpg`), illustrating the individual’s serial number and specific age. 16 | Individuals from serial number 00000 to 07380 are all female, from 07381 to 13321 are male. 17 | 18 | This dataset can be used for age prediction and gender classification. 19 | For fair comparison, we randomly split the images into two sets, one for trainning and the other for validation. 20 | The annotation files in folder `image sets` have the following format: 21 | `"%05dA%02d %d\n", person_id, age, gender,` 22 | where for gender, 0 stands for female and 1 stands for male. 23 | 24 | 25 | 26 | Please cite our [paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8620951) if you find this dataset useful for your research. 27 | ``` 28 | @article{cheng2019exploiting, 29 | title={Exploiting effective facial patches for robust gender recognition}, 30 | author={Cheng, Jingchun and Li, Yali and Wang, Jilong and Yu, Le and Wang, Shengjin}, 31 | journal={Tsinghua Science and Technology}, 32 | volume={24}, 33 | number={3}, 34 | pages={333--345}, 35 | year={2019}, 36 | publisher={TUP} 37 | } 38 | ``` 39 | -------------------------------------------------------------------------------- /illu_AAF.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JingchunCheng/All-Age-Faces-Dataset/67be4cdb6998c7f1538a4e1684bf5d3fd0816915/illu_AAF.png --------------------------------------------------------------------------------