1 citations · 2 across the 11 of their papers we have counts for
11 papers
Retrieval-Guided Generation for Safer Histopathology Image Captioning
Md. Enamul Hoq, Wataru Uegami, Saghir Alfasly +6
Generative vision-language models can produce fluent medical image captions but remain prone to hallucination, over-specific diagnostic claims, and factual inconsistency-serious is…
GIF: Generative Inspiration for Face Recognition at Scale
Saeed Ebrahimi, Sahar Rahimi, Ali Dabouei +3
Aiming to reduce the computational cost of Softmax in massive label space of Face Recognition (FR) benchmarks, recent studies estimate the output using a subset of identities. Alth…
Decomposed Distribution Matching in Dataset Condensation
Sahar Rahimi Malakshan, Mohammad Saeed Ebrahimi Saadabadi, Ali Dabouei +1
Dataset Condensation (DC) aims to reduce deep neural networks training efforts by synthesizing a small dataset such that it will be as effective as the original large dataset. Conv…
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…
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…
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…
Pose Attention-Guided Profile-to-Frontal Face Recognition
Moktari Mostofa, Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan +1
In recent years, face recognition systems have achieved exceptional success due to promising advances in deep learning architectures. However, they still fail to achieve expected a…
Information Maximization for Extreme Pose Face Recognition
Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Sobhan Soleymani +2
In this paper, we seek to draw connections between the frontal and profile face images in an abstract embedding space. We exploit this connection using a coupled-encoder network to…