For Masked face recognition work, i need a masked face dataset with classification labeling. where test/train/valid folder exist and each folder contain different persons subfolder with images.
Hi,
MAFA (MAsked FAces) is a masked face detection benchmark dataset, of which images are collected from Internet images. MAFA contains 30,811 images and 35,806 masked faces. Faces in the dataset have various various orientations and occlusion degrees, while at least one part of each face is occluded by a mask. In the annotation process, each image contains at least one face occluded by various types of masks, while the six main attributes of each masked face, including locations of faces, eyes and masks, face orientation, occlusion degree and mask type.
The dataset can be download via: http://www.escience.cn/people/geshiming/mafa.html
MAFA is better for face detection problem, because there all images are in a folder. But i need a masked face dataset which is helpful for face recognition problem, where each person has different folder with test and train. Dataset like-
https://www.kaggle.com/dansbecker/5-celebrity-faces-dataset#data.zip
@ Mark van Gastel
Hope u would have seen this link https://www.kairos.com/blog/60-facial-recognition-databases
Hi! Check out the Face Image Meta-Database (fIMDb): https://cliffordworkman.com/resources/
The fIMDb includes info or estimates on: number of photo sets per source (and numbers of neutral and other sets — e.g., facial emotions), number of subjects per source (with approximate sex distributions), total number of images, approximate number of viewpoints, whether the sources includes photos from more than one ethnicity, whether it includes more than one age group, whether meta-data are available, the photo category (e.g., posed, wild), the reference(s) for the source (e.g. DOIs). I hope this will aid others interested in conducting research on responses to faces.
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