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Mohsen Fayyaz

Research Intern at Microsoft, PhD Candidate, University of Bonn, Computer Vision Group of Prof. Dr. Juergen Gall

Google Scholar

About Me

Experienced Doctoral Researcher at the university of Bonn with a demonstrated history of working in the research industry. Skilled in Computer Vision and Deep Learning. Strong research professional with a Master’s Degree focused in Artificial Intelligence.

Selected Publications

Google Scholar

Long Short View Feature Decomposition via Contrastive Video RepresentationLearning

2021 - ICCV
N. Behrman, M. Fayyaz, J. Gall, M. Noroozi

Paper | Supplementary Material

Fast Weakly Supervised Action Segmentation Using Mutual Consistency

2021 - IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Y. Souri*, M. Fayyaz*, L. Minciullo, G. Francesca, J. Gall
*Equal contribution

Paper | Code

3D CNNs with Adaptive Temporal Feature Resolutions

2021 - CVPR
M. Fayyaz*, E. Bahrami*, A. Diba, M. Noroozi, E. Adeli, L. Van Gool, J. Gall
*Equal contribution

Paper | Project Page/Code

Large Scale Holistic Video Understanding

2020 - ECCV Spotlight (Top ~3%)
A. Diba*, M. Fayyaz*, V. Sharma*, M. Paluri, J. Gall, R. Stiefelhagen, L. Van Gool
*Equal contribution, listed in alphabetical order

Paper | Supplementary Document | Data | Project Website

SCT: Set Constrained Temporal Transformer for Set Supervised Action Segmentation

2020 - CVPR
M. Fayyaz and J. Gall

Paper | Code

AVID: Adversarial Visual Irregularity Detection

2018 - ACCV
M. Sabokrou*, M. Pourreza*, M. Fayyaz*, R. Entezari, R. Fathy, J. Gall, E. Adeli
*Equal contribution

Paper | Code

Spatio-Temporal Channel Correlation Networks for Action Classification

2018 - ECCV
A. Diba*, M. Fayyaz*, V. Sharma, M. Arzani, R. Yousefzadeh, J. Gall, L. Van Gool
*Equal contribution

Paper

Temporal 3D ConvNets by Temporal Transition Layer

2018 - CVPR Workshop on Brave New Ideas in Video Understanding 2018
A. Diba*, M. Fayyaz*, V. Sharma, A. Karami, M. Arzani, R. Yousefzadeh, L. Van Gool
*Equal contribution

Paper


Deep-anomaly: Fully convolutional neural network for fast anomaly detection in crowded scenes

2018 - Computer Vision and Image Understanding
M. Sabokro*, M. Fayyaz*, M. Fathy, Z. Moayed, R. Klette
*Equal contribution

Paper


Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet

2018 - arXiv
S.H. Hasanpour, M. Rouhani , M. Fayyaz, M. Sabokro, E. Adeli

Paper | Code


Deep-cascade: Cascading 3D Deep Neural Networks for Fast Anomaly Detection and Localization in Crowded Scenes

2017 - IEEE Transactions on Image Processing
M. Sabokro, M. Fayyaz, M. Fathy, R. Klette

Paper

STFCN - Spatio-Temporal Fully Convolutional Neural Network for Semantic Segmentation of Street Scenes

2016 - ACCV Workshop
M. Fayyaz, M. Sabokro, M. Hajizadeh, M. Fathy, F. Huang, R. Klette

Paper | Code

Workshops and Tutorials

Second Workshop on Large Scale Holistic Video Understanding

25th June 2021

In Conjunction with CVPR 2021

Organizers: Mohsen Fayyaz (University of Bonn), Vivek Sharma (KIT), Ali Diba (KU Leuven), Prof. Luc van Gool (KU Leuven, ETH Zurich), Prof. Jeurgen Gall (University of Bonn), Ehsan Adeli (Stanford), David Ross (Google AI), Prof. Rainer Stiefelhage (KIT), Manohar Paluri (Facebook)

Tutorial on Large Scale Holistic Video Understanding

Seattle, U.S., June 2020

In conjunction with CVPR 2020

Organizers: Mohsen Fayyaz (University of Bonn), Ali Diba (KU Leuven), Vivek Sharma (KIT), Prof. Luc van Gool (KU Leuven, ETH Zurich), Prof. Rainer Stiefelhage (KIT), Prof. Jeurgen Gall (University of Bonn), Manohar Paluri (Facebook)

Workshop on Large Scale Holistic Video Understanding

Seoul, Korea, 27th October 2019

In Conjunction with ICCV 2019

Organizers: Vivek Sharma (KIT), Mohsen Fayyaz (University of Bonn), Ali Diba (KU Leuven), Prof. Luc van Gool (KU Leuven, ETH Zurich), Prof. Jeurgen Gall (University of Bonn), Prof. Rainer Stiefelhage (KIT), Manohar Paluri (Facebook)

Experience

Microsoft

Research Intern

Computer vision research internship at Microsoft Applied Sciences Group, Perception Team, United Kingdom.

Bosch Center for Artificial Intelligence

Research Intern

Computer vision research internship at Bosch Center for Artificial Intelligence, Renningen, Germany.

Microsoft

Research Intern

Computer vision research internship at Microsoft, Redmond, Washington.

University of Bonn

Doctoral Researcher

Computer vision doctoral researcher at the University of Bonn, faculty of Computer Science III under supervision of Prof. Dr. J. Gall.

Sensifai

Computer Vision/ML Engineer

Designing and Developing Deep Neural Networks Architectures for Computer Vision Tasks.

Iran University of Science and Technology

Research Assistant

Machine learning and Deep learning researcher in IUST HPC lab with the supervision of Prof. M. Fathy.

Education

University of Bonn

November 2017 - Now

PhD Candidate, Computer Science

Supervisor: Prof. Dr. J. Gall

Master Students:

MUT

September 2014 - September 2016

Master of Science in Computer Science - Artificial Intelligence and Robotics

Supervisors: Prof. Mahmood Fathy , Dr. Mojtaba Hosseini
Advisor: Dr. Mohammad Sabokrou
Thesis: Activity Recognition in Video based on Convolutional Neural Networks
GPA: 19.13/20.00
Ranked First with highest GPA among all Computer Engineering students (AI) since 2014

Semnan University

September 2010 - September 2014

Bachelor of Science in Computer Software Engineering

Supervisor: Dr. K. Kiani
Thesis: Designing and Implementing a Cloud-based Accounting System
Ranked First with highest GPA among all of the university computer engineering students since 2010

Allameh Helli High School

2006 - 2010

Mathematics and Physics

National Organization for Development of Exceptional Talents (NODET)

Skills

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