Aamir Mustafa

Aamir Mustafa

PhD Student at University of Cambridge

UC

Latest News

1 paper accepted in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2020.

1 paper accepted in IEEE Transactions on Image Processing (TIP) 2020.

1 paper accepted in International Conference on Computer Vision (ICCV) 2019.

Publications

Deeply Supervised Discriminative Learning for Adversarial Defense

Authors: Aamir Mustafa, Salman Khan, Munawar Hayat, Roland Goecke, Jianbing Shen, Ling Shao

IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2020

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Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

Authors: Aamir Mustafa, Salman Khan, Munawar Hayat, Roland Goecke, Jianbing Shen, Ling Shao

International Conference on Computer Vision (ICCV) 2019

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Image Super-Resolution as a Defense against Adversarial Attacks

Authors: Aamir Mustafa, Salman Khan, Munawar Hayat, Jianbing Shen, Ling Shao

IEEE Transactions on Image Processing (TIP) 2020

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Prediction and Localization of Student Engagement in the Wild

Authors: Amanjot Kaur, Aamir Mustafa, Love Mehta, Abhinav Dhall

Digital Image Computing: Techniques and Applications (DICTA) 2018

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Heart Rate Estimation from Facial Videos for Depression Analysis.

Authors: Aamir Mustafa, Shalini Bhatia, Munawar Hayat, Roland Goecke

International Conference on Affective Computing and Intelligent Interaction (ACII) 2017

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Experience

PhD Student - Computer Science Dept. University of Cambridge (Oct 2019 - Present)

Leveraging the use of semi-supervised learing for image to image translation. .

Computer Vision Research Intern - Inception Institute of Artificial Intelligence (Sep 2018 - Sep 2019)

Working on making deep neural networks robust against adversarial attacks.

Computer Vision Research Intern - Indian Institute of Technology, Ropar (Dec 2017 - Mar 2018)

Worked on prediction and localization of student engagement in response to a stimuli video (e-learning environment) from facial expressions using Deep Multi-Instance Learning.

Machine Learning Research Intern - University of Canberra, Australia (Dec 2016 - Feb 2017)

Estimation of Heart rate of different individuals and its variations over the span of video from their facial videos by extracting plethysmograph (PG) signals from green channel of the frames. Considering heart rate as extracted feature, individuals are classified into two categories - healthy controls and depressed patients using a linear SVM classifier.

Bio

I did my bachelors degree in Electronics and Communication Engineering from National Institute of Technology (NIT), Srinagar, India. During my under-grad I did a couple of research intersnhips at University of Canberra, Australia and Indian Institute of Technology (IIT) Ropar. Later I am worked as a computer vision research intern at Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, UAE for a year. Currently I am working as a Research Assistant/ PhD candidate at University of Cambridge, UK on Applications of Machine/Deep Learning in Computer Graphics.