A Comprehensive Study on Occlusion Invariant Face Recognition under Face Mask Occlusion
Not on the map. Why?
Abstract (arXiv)
The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face, and it makes it difficult to recognize them even for humans. The evaluation report shows the difficulty well when recognizing masked faces. Rapid development and breakthrough of deep learning in the recent past have witnessed most promising results from face recognition algorithms. But they fail to perform far from satisfactory levels in the unconstrained environment during the challenges such as varying lighting conditions, low resolution, facial expressions, pose variation and occlusions. Facial occlusions are considered one of the most intractable problems. Especially when the occlusion occupies a large region of the face because it destroys lots of official features.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 9 of its 24 references that are in the map. First posted on arXiv 22 Jan 2022.
Builds on
9 of 24 references.
References · 9
- 2017SphereFace: Deep Hypersphere Embedding for Face Recognitioncited by 733
- 2018Deep Face Recognition: A Surveycited by 275
- 2020Masked Face Recognition Dataset and Applicationcited by 66
- 2019Occlusion Robust Face Recognition Based on Mask Learning with PairwiseDifferential Siamese Networkcited by 51
- 2020Masked Face Recognition for Secure Authenticationcited by 47
- 2020A survey of face recognition techniques under occlusioncited by 38
- 2020The Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Studycited by 26
- 2015Targeting Ultimate Accuracy: Face Recognition via Deep Embeddingcited by 18
- 2017Enhancing Convolutional Neural Networks for Face Recognition with Occlusion Maps and Batch Triplet Losscited by 9
Built on by
Citing papers per year: 2023: 1.
1 paper.