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20192025
most citedFacial Expression Recognition Using Disentangled Adversarial Learning

8 citations · 26 across the 9 of their papers we have counts for

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cs.CV2025

HyRet-Change: A hybrid retentive network for remote sensing change detection

Mustansar Fiaz, Mubashir Noman, Hiyam Debary +2

Recently convolution and transformer-based change detection (CD) methods provide promising performance. However, it remains unclear how the local and global dependencies interact t…

cs.CV20248 cited

A Survey of the Self Supervised Learning Mechanisms for Vision Transformers

Asifullah Khan, Anabia Sohail, Mustansar Fiaz +11

Advances in deep learning are re-defining how visual data is processed and understand by the machines. Vision Transformers (ViTs) have recently demonstrated prominent performance i…

cs.CV20231 cited

A Unified Transformer-based Network for multimodal Emotion Recognition

Kamran Ali, Charles E. Hughes

The development of transformer-based models has resulted in significant advances in addressing various vision and NLP-based research challenges. However, the progress made in trans…

cs.CV20201 cited

An Efficient Integration of Disentangled Attended Expression and Identity FeaturesFor Facial Expression Transfer andSynthesis

Kamran Ali, Charles E. Hughes

In this paper, we present an Attention-based Identity Preserving Generative Adversarial Network (AIP-GAN) to overcome the identity leakage problem from a source image to a generate…

cs.CV20191 cited

Facial Expression Representation Learning by Synthesizing Expression Images

Kamran Ali, Charles E. Hughes

Representations used for Facial Expression Recognition (FER) usually contain expression information along with identity features. In this paper, we propose a novel Disentangled Exp…

cs.CV20197 cited

All-In-One: Facial Expression Transfer, Editing and Recognition Using A Single Network

Kamran Ali, Charles E. Hughes

In this paper, we present a unified architecture known as Transfer-Editing and Recognition Generative Adversarial Network (TER-GAN) which can be used: 1. to transfer facial express…