Analysis of face detection, face landmarking, and face recognition performance with masked face images
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Abstract (arXiv)
Face recognition has become an essential task in our lives. However, the current COVID-19 pandemic has led to the widespread use of face masks. The effect of wearing face masks is currently an understudied issue. The aim of this paper is to analyze face detection, face landmarking, and face recognition performance with masked face images. HOG and CNN face detectors are used for face detection in combination with 5-point and 68-point face landmark predictors and VGG16 face recognition model is used for face recognition on masked and unmasked images. We found that the performance of face detection, face landmarking, and face recognition is negatively impacted by face masks
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 19 references that are in the map. First posted on arXiv 3 Jun 2022.
Builds on
8 of 19 references.
References · 8
- 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,833
- 2017SphereFace: Deep Hypersphere Embedding for Face Recognitioncited by 733
- 2020Masked Face Recognition Dataset and Applicationcited by 66
- 2015DeepID3: Face Recognition with Very Deep Neural Networkscited by 62
- 2019Occlusion Robust Face Recognition Based on Mask Learning with PairwiseDifferential Siamese Networkcited by 51
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- 2016Grid Loss: Detecting Occluded Facescited by 17
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Citing papers per year: 2024: 1.
1 paper.