SOF: A Synthetic Occluded Face Dataset

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Mengmeng Duan, Yan Wang, Lurui Jin, Yuan Wu

Published: 2021, Last Modified: 01 Mar 2026IEEE BigData 2021EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: In this paper, we propose an occluded face dataset named SOF (Synthetic Occluded Face) and describe in detail the construction method of SOF. We synthesize the occluded image into the face image after the thin plate spline deformation to obtain the occluded face image, and then make the image more real through guided filter. At the end of this paper, we use the SOF training set and general face datasets Ms-Celeb-1M, CASIA-WebFace to train the mainstream face recognition algorithms FaceNet, SphereFace and ArcFace, and test on a variety of test sets. A series of experiments proved that the occluded face dataset generated by this method could improve the accuracy of occluded face recognition of mainstream face recognition algorithms.