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20152024
most cited3D Convolutional Neural Networks for Cross Audio-Visual Matching Recognition

119 citations · 374 across the 48 of their papers we have counts for

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cs.CV2023

Trading-off Mutual Information on Feature Aggregation for Face Recognition

Mohammad Akyash, Ali Zafari, Nasser M. Nasrabadi

Despite the advances in the field of Face Recognition (FR), the precision of these methods is not yet sufficient. To improve the FR performance, this paper proposes a technique to…

cs.CV2023

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…

cs.CV2023

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…

cs.CV20231 cited

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…

cs.CV2023

AAFACE: Attribute-aware Attentional Network for Face Recognition

Niloufar Alipour Talemi, Hossein Kashiani, Sahar Rahimi Malakshan +4

In this paper, we present a new multi-branch neural network that simultaneously performs soft biometric (SB) prediction as an auxiliary modality and face recognition (FR) as the ma…

cs.CV2023

Improving Face Recognition from Caption Supervision with Multi-Granular Contextual Feature Aggregation

Md Mahedi Hasan, Nasser Nasrabadi

We introduce caption-guided face recognition (CGFR) as a new framework to improve the performance of commercial-off-the-shelf (COTS) face recognition (FR) systems. In contrast to c…