Search Results for author: Mohsen Fayyaz

Found 25 papers, 14 papers with code

RET-LLM: Towards a General Read-Write Memory for Large Language Models

1 code implementation23 May 2023 Ali Modarressi, Ayyoob Imani, Mohsen Fayyaz, Hinrich Schütze

Large language models (LLMs) have significantly advanced the field of natural language processing (NLP) through their extensive parameters and comprehensive data utilization.

Question Answering

Diffusion Models for Medical Image Analysis: A Comprehensive Survey

1 code implementation14 Nov 2022 Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari, Reza Azad, Mohsen Fayyaz, Ilker Hacihaliloglu, Dorit Merhof

Then, we provide a systematic taxonomy of diffusion models in the medical domain and propose a multi-perspective categorization based on their application, imaging modality, organ of interest, and algorithms.

Denoising Navigate

Metaphors in Pre-Trained Language Models: Probing and Generalization Across Datasets and Languages

1 code implementation ACL 2022 Ehsan Aghazadeh, Mohsen Fayyaz, Yadollah Yaghoobzadeh

Large pre-trained language models (PLMs) are therefore assumed to encode metaphorical knowledge useful for NLP systems.

Adaptive Token Sampling For Efficient Vision Transformers

1 code implementation30 Nov 2021 Mohsen Fayyaz, Soroush Abbasi Koohpayegani, Farnoush Rezaei Jafari, Sunando Sengupta, Hamid Reza Vaezi Joze, Eric Sommerlade, Hamed Pirsiavash, Juergen Gall

Since ATS is a parameter-free module, it can be added to the off-the-shelf pre-trained vision transformers as a plug and play module, thus reducing their GFLOPs without any additional training.

Image Classification Video Classification

TaylorSwiftNet: Taylor Driven Temporal Modeling for Swift Future Frame Prediction

no code implementations27 Oct 2021 Saber Pourheydari, Emad Bahrami, Mohsen Fayyaz, Gianpiero Francesca, Mehdi Noroozi, Juergen Gall

While recurrent neural networks (RNNs) demonstrate outstanding capabilities for future video frame prediction, they model dynamics in a discrete time space, i. e., they predict the frames sequentially with a fixed temporal step.

Long Short View Feature Decomposition via Contrastive Video Representation Learning

no code implementations ICCV 2021 Nadine Behrmann, Mohsen Fayyaz, Juergen Gall, Mehdi Noroozi

We argue that a single representation to capture both types of features is sub-optimal, and propose to decompose the representation space into stationary and non-stationary features via contrastive learning from long and short views, i. e. long video sequences and their shorter sub-sequences.

Action Recognition Action Segmentation +2

Not All Models Localize Linguistic Knowledge in the Same Place: A Layer-wise Probing on BERToids' Representations

no code implementations13 Sep 2021 Mohsen Fayyaz, Ehsan Aghazadeh, Ali Modarressi, Hosein Mohebbi, Mohammad Taher Pilehvar

Most of the recent works on probing representations have focused on BERT, with the presumption that the findings might be similar to the other models.

3D CNNs with Adaptive Temporal Feature Resolutions

1 code implementation CVPR 2021 Mohsen Fayyaz, Emad Bahrami, Ali Diba, Mehdi Noroozi, Ehsan Adeli, Luc van Gool, Juergen Gall

While the GFLOPs of a 3D CNN can be decreased by reducing the temporal feature resolution within the network, there is no setting that is optimal for all input clips.

Action Recognition

Large Scale Holistic Video Understanding

1 code implementation ECCV 2020 Ali Diba, Mohsen Fayyaz, Vivek Sharma, Manohar Paluri, Jurgen Gall, Rainer Stiefelhagen, Luc van Gool

HVU is organized hierarchically in a semantic taxonomy that focuses on multi-label and multi-task video understanding as a comprehensive problem that encompasses the recognition of multiple semantic aspects in the dynamic scene.

Action Classification Action Recognition +7

Online Signature Verification using Deep Representation: A new Descriptor

no code implementations24 Jun 2018 Mohammad Hajizadeh Saffar, Mohsen Fayyaz, Mohammad Sabokrou, Mahmood Fathy

To deal with these difficulties and modeling the signatures efficiently, we propose a method that a one-class classifier per each user is built on discriminative features.

One-class classifier

Spatio-Temporal Channel Correlation Networks for Action Classification

no code implementations ECCV 2018 Ali Diba, Mohsen Fayyaz, Vivek Sharma, M. Mahdi Arzani, Rahman Yousefzadeh, Juergen Gall, Luc van Gool

Our experiments show that adding STC blocks to current state-of-the-art architectures outperforms the state-of-the-art methods on the HMDB51, UCF101 and Kinetics datasets.

Action Classification Classification +1

Semantic Video Segmentation: A Review on Recent Approaches

no code implementations16 Jun 2018 Mohammad Hajizadeh Saffar, Mohsen Fayyaz, Mohammad Sabokrou, Mahmood Fathy

This paper gives an overview on semantic segmentation consists of an explanation of this field, it's status and relation with other vision fundamental tasks, different datasets and common evaluation parameters that have been used by researchers.

Semantic Segmentation Video Segmentation +1

AVID: Adversarial Visual Irregularity Detection

2 code implementations24 May 2018 Mohammad Sabokrou, Masoud Pourreza, Mohsen Fayyaz, Rahim Entezari, Mahmood Fathy, Jürgen Gall, Ehsan Adeli

Real-time detection of irregularities in visual data is very invaluable and useful in many prospective applications including surveillance, patient monitoring systems, etc.

Anomaly Detection

Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet

4 code implementations17 Feb 2018 Seyyed Hossein Hasanpour, Mohammad Rouhani, Mohsen Fayyaz, Mohammad Sabokrou, Ehsan Adeli

SimpNet outperforms the deeper and more complex architectures such as VGGNet, ResNet, WideResidualNet \etc, on several well-known benchmarks, while having 2 to 25 times fewer number of parameters and operations.

Image Classification

Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification

3 code implementations22 Nov 2017 Ali Diba, Mohsen Fayyaz, Vivek Sharma, Amir Hossein Karami, Mohammad Mahdi Arzani, Rahman Yousefzadeh, Luc van Gool

Thus, by finetuning this network, we beat the performance of generic and recent methods in 3D CNNs, which were trained on large video datasets, e. g. Sports-1M, and finetuned on the target datasets, e. g. HMDB51/UCF101.

Action Recognition General Classification +3

Lets keep it simple, Using simple architectures to outperform deeper and more complex architectures

9 code implementations22 Aug 2016 Seyyed Hossein Hasanpour, Mohammad Rouhani, Mohsen Fayyaz, Mohammad Sabokrou

Our simple 13-layer architecture outperforms most of the deeper and complex architectures to date such as VGGNet, ResNet, and GoogleNet on several well-known benchmarks while having 2 to 25 times fewer number of parameters and operations.

Image Classification

STFCN: Spatio-Temporal FCN for Semantic Video Segmentation

1 code implementation21 Aug 2016 Mohsen Fayyaz, Mohammad Hajizadeh Saffar, Mohammad Sabokrou, Mahmood Fathy, Reinhard klette, Fay Huang

Current work on convolutional neural networks(CNNs) has shown that CNNs provide advanced spatial features supporting a very good performance of solutions for both image and video analysis, especially for the semantic segmentation task.

Semantic Segmentation Video Segmentation +1

Feature Representation for Online Signature Verification

no code implementations29 May 2015 Mohsen Fayyaz, Mohammad Hajizadeh_Saffar, Mohammad Sabokrou, Mahmood Fathy

Biometrics systems have been used in a wide range of applications and have improved people authentication.

feature selection

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