no code implementations • 29 Oct 2022 • Seyed Mehdi Iranmanesh, Xiaotong Chen, Kuo-Chin Lien
In this approach, we detect an object bounding box as a pair of keypoints, the top-left corner and the center, using two decoders.
no code implementations • 1 Jan 2022 • Xiaotong Chen, Seyed Mehdi Iranmanesh, Kuo-Chin Lien
In this paper, we present PatchTrack, a Transformer-based joint-detection-and-tracking system that predicts tracks using patches of the current frame of interest.
no code implementations • 10 Dec 2021 • Sobhan Soleymani, Ali Dabouei, Fariborz Taherkhani, Seyed Mehdi Iranmanesh, Jeremy Dawson, Nasser M. Nasrabadi
The first loss assures that the representations of modalities for a class have comparable magnitudes to provide a better quality estimation, while the multimodal representations of different classes are distributed to achieve maximum discrimination in the embedding space.
no code implementations • 7 Feb 2021 • Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi
However, GANs overlook the explicit data density characteristics which leads to undesirable quantitative evaluations and mode collapse.
no code implementations • 4 Sep 2020 • Seyed Mehdi Iranmanesh, Ali Dabouei, Nasser M. Nasrabadi
We present a novel framework to exploit privileged information for recognition which is provided only during the training phase.
no code implementations • 7 Jan 2020 • Seyed Mehdi Iranmanesh, Ali Dabouei, Sobhan Soleymani, Hadi Kazemi, Nasser M. Nasrabadi
In this work, we present a practical approach to the problem of facial landmark detection.
1 code implementation • 27 Nov 2019 • Ali Borji, Seyed Mehdi Iranmanesh
Object detection remains as one of the most notorious open problems in computer vision.
no code implementations • 27 Jul 2019 • Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi
In this paper, we present an attribute-guided deep coupled learning framework to address the problem of matching polarimetric thermal face photos against a gallery of visible faces.
no code implementations • NeurIPS 2018 • Hadi Kazemi, Sobhan Soleymani, Fariborz Taherkhani, Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi
These approaches usually fail to model domain-specific information which has no representation in the target domain.
no code implementations • 14 Nov 2018 • Hadi Kazemi, Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi
This paper describes the Style and Content Disentangled GAN (SC-GAN), a new unsupervised algorithm for training GANs that learns disentangled style and content representations of the data.
no code implementations • 31 Jul 2018 • Ali Dabouei, Sobhan Soleymani, Hadi Kazemi, Seyed Mehdi Iranmanesh, Jeremy Dawson, Nasser M. Nasrabadi
We achieved the rank-10 accuracy of 88. 02\% on the IIIT-Delhi latent fingerprint database for the task of latent-to-latent matching and rank-50 accuracy of 70. 89\% on the IIIT-Delhi MOLF database for the task of latent-to-sensor matching.
no code implementations • 31 Jul 2018 • Sobhan Soleymani, Ali Dabouei, Seyed Mehdi Iranmanesh, Hadi Kazemi, Jeremy Dawson, Nasser M. Nasrabadi
In this paper a novel cross-device text-independent speaker verification architecture is proposed.
no code implementations • 31 Jul 2018 • Seyed Mehdi Iranmanesh, Hadi Kazemi, Sobhan Soleymani, Ali Dabouei, Nasser M. Nasrabadi
The proposed Attribute-Assisted Deep Con- volutional Neural Network (AADCNN) method exploits the facial attributes and leverages the loss functions from the facial attributes identification and face verification tasks in order to learn rich discriminative features in a common em- bedding subspace.
no code implementations • 4 Jan 2018 • Seyed Mehdi Iranmanesh, Ali Dabouei, Hadi Kazemi, Nasser M. Nasrabadi
we propose a coupled deep neural network architecture which leverages relatively large visible and thermal datasets to overcome the problem of overfitting and eventually we train it by a polarimetric thermal face dataset which is the first of its kind.
no code implementations • 3 Jan 2018 • Ali Dabouei, Hadi Kazemi, Seyed Mehdi Iranmanesh, Jeremi Dawson, Nasser M. Nasrabadi
Elastic distortion of fingerprints has a negative effect on the performance of fingerprint recognition systems.
no code implementations • NeurIPS 2017 • Saeid Motiian, Quinn Jones, Seyed Mehdi Iranmanesh, Gianfranco Doretto
This work provides a framework for addressing the problem of supervised domain adaptation with deep models.
2 code implementations • 18 Jun 2017 • Amirsina Torfi, Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi, Jeremy Dawson
We propose the use of a coupled 3D Convolutional Neural Network (3D-CNN) architecture that can map both modalities into a representation space to evaluate the correspondence of audio-visual streams using the learned multimodal features.