11 citations · 13 across the 9 of their papers we have counts for
9 papers
Boosting Unconstrained Face Recognition with Targeted Style Adversary
Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Seyed Rasoul Hosseini +1
While deep face recognition models have demonstrated remarkable performance, they often struggle on the inputs from domains beyond their training data. Recent attempts aim to expan…
ARoFace: Alignment Robustness to Improve Low-Quality Face Recognition
Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Ali Dabouei +1
Aiming to enhance Face Recognition (FR) on Low-Quality (LQ) inputs, recent studies suggest incorporating synthetic LQ samples into training. Although promising, the quality factors…
Hyperspherical Classification with Dynamic Label-to-Prototype Assignment
Mohammad Saeed Ebrahimi Saadabadi, Ali Dabouei, Sahar Rahimi Malakshan +1
Aiming to enhance the utilization of metric space by the parametric softmax classifier, recent studies suggest replacing it with a non-parametric alternative. Although a non-parame…
Towards Generalizable Morph Attack Detection with Consistency Regularization
Hossein Kashiani, Niloufar Alipour Talemi, Mohammad Saeed Ebrahimi Saadabadi +1
Though recent studies have made significant progress in morph attack detection by virtue of deep neural networks, they often fail to generalize well to unseen morph attacks. With n…
Deep Boosting Multi-Modal Ensemble Face Recognition with Sample-Level Weighting
Sahar Rahimi Malakshan, Mohammad Saeed Ebrahimi Saadabadi, Nima Najafzadeh +1
Deep convolutional neural networks have achieved remarkable success in face recognition (FR), partly due to the abundant data availability. However, the current training benchmarks…
CCFace: Classification Consistency for Low-Resolution Face Recognition
Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Hossein Kashiani +1
In recent years, deep face recognition methods have demonstrated impressive results on in-the-wild datasets. However, these methods have shown a significant decline in performance…