Masked Face Segmentation Dataset
During the covid-19 era wearing face masks posed new challenges to face-related tasks, including facial recognition, face inpainting, expression
recognition, and object removal.
Mask region segmentation is a preliminary stage to tackle the occlusion issue corresponding to the face-related tasks.
Existing masked face datasets are not procedure binary segmentation maps because Segmenting mask regions manually is a time-consuming operation. As a result, existing unmasking methods; synthesize training data by overlaying masks on existing face datasets. However, since these techniques rely on an artificially generated mask, their effects tend to seem unnatural. To address this issue, the masked face segmentation dataset(MFSD) provides the first public training dataset for the mask segmentation task.
Variants: MFSD
This dataset is used in 1 benchmark:
No recent benchmark submissions available for this dataset.
No papers with results on this dataset found.