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Found 8 papers, 1 papers with code
Are Face Detection Models Biased?
Since facial region localization is an essential task for all face recognition pipelines, it is imperative to analyze the presence of such bias in popular deep models.
Anatomizing Bias in Facial Analysis
In this paper, we encapsulate bias detection/estimation and mitigation algorithms for facial analysis.
Unravelling the Effect of Image Distortions for Biased Prediction of Pre-trained Face Recognition Models
We provide a systematic analysis to evaluate the performance of four state-of-the-art deep face recognition models in the presence of image distortions across different \textit{gender} and \textit{race} subgroups.
Indian Masked Faces in the Wild Dataset
We have also benchmarked the performance of existing face recognition models on the proposed IMFW dataset.
Class Equilibrium using Coulomb's Law
Projection algorithms learn a transformation function to project the data from input space to the feature space, with the objective of increasing the inter-class distance.
Subclass Contrastive Loss for Injured Face Recognition
Deaths and injuries are common in road accidents, violence, and natural disaster.
Multi-Task Driven Explainable Diagnosis of COVID-19 using Chest X-ray Images
Firstly, we present the COVID-19 Multi-Task Network which is an automated end-to-end network for COVID-19 screening.
Data Fine-tuning
Stimulated by the advances in adversarial perturbations, this research proposes the concept of Data Fine-tuning to improve the classification accuracy of a given model without changing the parameters of the model.
