Welcome!
Welcome to the Multi-Attribute Labelled Faces (abbreviated as MALF), which is a large dataset designed for fine-grained evaluation of face detection in the wild. This website provides:
Descriptions
Images
The dataset contains 5,250 images with 11,931 annotated faces collected from the Internet.
Annotations
Each face contains the following annotations:
For more details about the database and its annotation statistics, please refer to our evaluation paper.
Go to examples for a quick look at the dataset.
Evaluation
The dataset has been splitted into two parts, 5,000 test images for evaluation and 250 example images with annotations for finetuning the algorithm and/or adjusting the output bounding box style.
Evaluation procedures
Performance measurement
For more details about the evaluation protocol and rules, please refer to our evaluation paper.
Reference
If you use our dataset or evaluation results in your work, please cite our evaluation paper:
Bin Yang*, Junjie Yan*, Zhen Lei and Stan Z. Li.
Fine-grained Evaluation on Face Detection in the Wild.
Proceedings of the 11th IEEE International Conference on Automatic Face and Gesture Recognition Conference and Workshops.
BibTex entry:
@inproceedings{faceevaluation15, title={Fine-grained Evaluation on Face Detection in the Wild}, author={Yang, Bin and Yan, Junjie and Lei, Zhen and Li, Stan Z}, booktitle={Automatic Face and Gesture Recognition (FG), 11th IEEE International Conference on}, year={2015}, organization={IEEE} }
Organizers
Junjie Yan [page]
Bin Yang [page]
Zhen Lei [page]
Stan Z. Li (Advisor) [page]
News!
29/9/15: We add fine-grained results with regard to different views, check it out at Results page!
13/5/15: MALF is now a public benchmark. New submissions are always welcome!
13/3/15: Curves data available!
29/1/15: FG2015 Evaluation finished! 21 state-of-the-art algorithms are evaluated!
10/9/14: Dataset upgraded! 13/4/14: This face detection evaluation is part of the evaluations in FG2015.
Contact us
Zhen Lei: zlei[at]nlpr.ia.ac.cn
Bin Yang: yb.derek[at]gmail.com
Junjie Yan: yanjjie[at]gmail.com