HiMFR: A Hybrid Masked Face Recognition Through Face Inpainting

@article{Hosen2022HiMFRAH,
  title={HiMFR: A Hybrid Masked Face Recognition Through Face Inpainting},
  author={Md Imran Hosen and Md Baharul Islam},
  journal={ArXiv},
  year={2022},
  volume={abs/2209.08930}
}
—To recognize the masked face, one of the possible solutions could be to restore the occluded part of the face first and then apply the face recognition method. Inspired by the recent image inpainting methods, we propose an end-to-end hybrid masked face recognition system, namely HiMFR, consisting of three significant parts: masked face detector, face inpainting, and face recognition. The masked face detector module applies a pretrained Vision Transformer (ViT b32) to detect whether faces are… 
[PDF] Semantic Reader

Figures and Tables from this paper

References

SHOWING 1-10 OF 24 REFERENCES

Deep Covariance Feature and CNN-based End-to-End Masked Face Recognition

An automated Masked Face Recognition (MFR) system based on the combination of a mask occlusion discarding technique and a deep-learning model that achieves its competitive performance compared to the state-of-the-art.

A Novel GAN-Based Network for Unmasking of Masked Face

The objective of this work is to remove mask objects in facial images by employing a GAN-based network using two discriminators where one discriminator helps learn the global structure of the face and then another discriminator comes in to focus learning on the deep missing region.

Boosting Masked Face Recognition with Multi-Task ArcFace

Experimental results show that the proposed approach highly boosts the original model accuracy when dealing with masked faces, while preserving almost the same accuracy on the original non-masked datasets.

Occlusion Robust Face Recognition Based on Mask Learning With Pairwise Differential Siamese Network

Comprehensive experiments on both synthesized and realistic occluded face datasets show that the proposed algorithm significantly outperforms the state-of-the-art systems.

Masked Face Recognition Dataset and Application

A multi-granularity masked face recognition model is developed that achieves 95% accuracy, exceeding the results reported by the industry and is currently the world's largest real-world masked face dataset.

Post-COVID-19 Mask-Aware Face Recognition System

Evaluation of the three hand-crafted descriptors and performance due to the proposed dynamic ensemble model (in the presence and absence of mask) is at par with the performance of the baseline face recognition system in the absence of facial mask.

SSDMNV2: A real time DNN-based face mask detection system using single shot multibox detector and MobileNetV2

Deep Learning Face Attributes in the Wild

A novel deep learning framework for attribute prediction in the wild that cascades two CNNs, LNet and ANet, which are fine-tuned jointly with attribute tags, but pre-trained differently.

SphereFace: Deep Hypersphere Embedding for Face Recognition

This paper proposes the angular softmax (A-Softmax) loss that enables convolutional neural networks (CNNs) to learn angularly discriminative features in deep face recognition (FR) problem under open-set protocol.

Generative Image Inpainting with Contextual Attention

This work proposes a new deep generative model-based approach which can not only synthesize novel image structures but also explicitly utilize surrounding image features as references during network training to make better predictions.