20 citations · 60 across the 24 of their papers we have counts for
34 papers
Landmark Enforcement and Style Manipulation for Generative Morphing
Samuel Price, Sobhan Soleymani, Nasser M. Nasrabadi
Morph images threaten Facial Recognition Systems (FRS) by presenting as multiple individuals, allowing an adversary to swap identities with another subject. Morph generation using…
Robust Ensemble Morph Detection with Domain Generalization
Hossein Kashiani, Shoaib Meraj Sami, Sobhan Soleymani +1
Although a substantial amount of studies is dedicated to morph detection, most of them fail to generalize for morph faces outside of their training paradigm. Moreover, recent morph…
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…
Revisiting Outer Optimization in Adversarial Training
Ali Dabouei, Fariborz Taherkhani, Sobhan Soleymani +1
Despite the fundamental distinction between adversarial and natural training (AT and NT), AT methods generally adopt momentum SGD (MSGD) for the outer optimization. This paper aims…
Benchmarking Human Face Similarity Using Identical Twins
Shoaib Meraj Sami, John McCauley, Sobhan Soleymani +2
The problem of distinguishing identical twins and non-twin look-alikes in automated facial recognition (FR) applications has become increasingly important with the widespread adopt…
Quality-Aware Multimodal Biometric Recognition
Sobhan Soleymani, Ali Dabouei, Fariborz Taherkhani +3
We present a quality-aware multimodal recognition framework that combines representations from multiple biometric traits with varying quality and number of samples to achieve incre…
Morph Detection Enhanced by Structured Group Sparsity
Poorya Aghdaie, Baaria Chaudhary, Sobhan Soleymani +2
In this paper, we consider the challenge of face morphing attacks, which substantially undermine the integrity of face recognition systems such as those adopted for use in border p…
Adversarially Perturbed Wavelet-based Morphed Face Generation
Kelsey O'Haire, Sobhan Soleymani, Baaria Chaudhary +3
Morphing is the process of combining two or more subjects in an image in order to create a new identity which contains features of both individuals. Morphed images can fool Facial…
Tasks Structure Regularization in Multi-Task Learning for Improving Facial Attribute Prediction
Fariborz Taherkhani, Ali Dabouei, Sobhan Soleymani +2
The great success of Convolutional Neural Networks (CNN) for facial attribute prediction relies on a large amount of labeled images. Facial image datasets are usually annotated by…
Attribute Guided Sparse Tensor-Based Model for Person Re-Identification
Fariborz Taherkhani, Ali Dabouei, Sobhan Soleymani +2
Visual perception of a person is easily influenced by many factors such as camera parameters, pose and viewpoint variations. These variations make person Re-Identification (ReID) a…
Attention Aware Wavelet-based Detection of Morphed Face Images
Poorya Aghdaie, Baaria Chaudhary, Sobhan Soleymani +2
Morphed images have exploited loopholes in the face recognition checkpoints, e.g., Credential Authentication Technology (CAT), used by Transportation Security Administration (TSA),…
Differential Morph Face Detection using Discriminative Wavelet Sub-bands
Baaria Chaudhary, Poorya Aghdaie, Sobhan Soleymani +2
Face recognition systems are extremely vulnerable to morphing attacks, in which a morphed facial reference image can be successfully verified as two or more distinct identities. In…
Detection of Morphed Face Images Using Discriminative Wavelet Sub-bands
Poorya Aghdaie, Baaria Chaudhary, Sobhan Soleymani +2
This work investigates the well-known problem of morphing attacks, which has drawn considerable attention in the biometrics community. Morphed images have exposed face recognition…
Differential Morphed Face Detection Using Deep Siamese Networks
Sobhan Soleymani, Baaria Chaudhary, Ali Dabouei +2
Although biometric facial recognition systems are fast becoming part of security applications, these systems are still vulnerable to morphing attacks, in which a facial reference i…
Mutual Information Maximization on Disentangled Representations for Differential Morph Detection
Sobhan Soleymani, Ali Dabouei, Fariborz Taherkhani +2
In this paper, we present a novel differential morph detection framework, utilizing landmark and appearance disentanglement. In our framework, the face image is represented in the…
SuperMix: Supervising the Mixing Data Augmentation
Ali Dabouei, Sobhan Soleymani, Fariborz Taherkhani +1
This paper presents a supervised mixing augmentation method termed SuperMix, which exploits the salient regions within input images to construct mixed training samples. SuperMix is…
Boosting Deep Face Recognition via Disentangling Appearance and Geometry
Ali Dabouei, Fariborz Taherkhani, Sobhan Soleymani +2
In this paper, we propose a framework for disentangling the appearance and geometry representations in the face recognition task. To provide supervision for this aim, we generate g…
Robust Facial Landmark Detection via Aggregation on Geometrically Manipulated Faces
Seyed Mehdi Iranmanesh, Ali Dabouei, Sobhan Soleymani +2
In this work, we present a practical approach to the problem of facial landmark detection. The proposed method can deal with large shape and appearance variations under the rich sh…
SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations
Ali Dabouei, Sobhan Soleymani, Fariborz Taherkhani +2
Deep neural networks are susceptible to adversarial manipulations in the input domain. The extent of vulnerability has been explored intensively in cases of -bounded and $\…
Defending Against Adversarial Iris Examples Using Wavelet Decomposition
Sobhan Soleymani, Ali Dabouei, Jeremy Dawson +1
Deep neural networks have presented impressive performance in biometric applications. However, their performance is highly at risk when facing carefully crafted input samples known…
Adversarial Examples to Fool Iris Recognition Systems
Sobhan Soleymani, Ali Dabouei, Jeremy Dawson +1
Adversarial examples have recently proven to be able to fool deep learning methods by adding carefully crafted small perturbation to the input space image. In this paper, we study…
Learning to Authenticate with Deep Multibiometric Hashing and Neural Network Decoding
Veeru Talreja, Sobhan Soleymani, Matthew C. Valenti +1
In this paper, we propose a novel multimodal deep hashing neural decoder (MDHND) architecture, which integrates a deep hashing framework with a neural network decoder (NND) to crea…
GASL: Guided Attention for Sparsity Learning in Deep Neural Networks
Amirsina Torfi, Rouzbeh A. Shirvani, Sobhan Soleymani +1
The main goal of network pruning is imposing sparsity on the neural network by increasing the number of parameters with zero value in order to reduce the architecture size and the…
Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound
Hadi Kazemi, Sobhan Soleymani, Fariborz Taherkhani +2
Unsupervised image-to-image translation is a class of computer vision problems which aims at modeling conditional distribution of images in the target domain, given a set of unpair…