Search Results for author: Hazim Kemal Ekenel

Found 37 papers, 16 papers with code

Exposure Correction Model to Enhance Image Quality

1 code implementation22 Apr 2022 Fevziye Irem Eyiokur, Dogucan Yaman, Hazim Kemal Ekenel, Alexander Waibel

We show that after applying exposure correction with the proposed model, the portrait matting quality increases significantly.

Image Matting

A Mobile Food Recognition System for Dietary Assessment

no code implementations20 Apr 2022 Şeymanur Aktı, Marwa Qaraqe, Hazim Kemal Ekenel

With the model achieving 94% accuracy on 23 food classes, the developed mobile application has potential to serve the visually impaired in automatic food recognition via images.

Data Augmentation Food Recognition

Fight Detection from Still Images in the Wild

1 code implementation16 Nov 2021 Şeymanur Aktı, Ferda Ofli, Muhammad Imran, Hazim Kemal Ekenel

We also propose a new dataset, named Social Media Fight Images (SMFI), comprising real-world images of fight actions.

Shuffled Patch-Wise Supervision for Presentation Attack Detection

no code implementations8 Sep 2021 Alperen Kantarcı, Hasan Dertli, Hazim Kemal Ekenel

We tested the proposed method both on the standard benchmark datasets -- Replay-Mobile, OULU-NPU -- and on a real-world dataset.

Face Anti-Spoofing Frame

On Recognizing Occluded Faces in the Wild

1 code implementation8 Sep 2021 Mustafa Ekrem Erakin, Uğur Demir, Hazim Kemal Ekenel

In this paper, we present the Real World Occluded Faces (ROF) dataset, that contains faces with both upper face occlusion, due to sunglasses, and lower face occlusion, due to masks.

Face Recognition

Alpha Matte Generation from Single Input for Portrait Matting

no code implementations6 Jun 2021 Dogucan Yaman, Hazim Kemal Ekenel, Alexander Waibel

We first generate a coarse segmentation map from the input image and then predict the alpha matte by utilizing the image and segmentation map.

Image Matting

Unconstrained Face-Mask & Face-Hand Datasets: Building a Computer Vision System to Help Prevent the Transmission of COVID-19

1 code implementation16 Mar 2021 Fevziye Irem Eyiokur, Hazim Kemal Ekenel, Alexander Waibel

To train and evaluate the developed system, we collected and annotated images that represent face mask usage and face-hand interaction in the real world.

MOCCA: Multi-Layer One-Class ClassificAtion for Anomaly Detection

1 code implementation9 Dec 2020 Fabio Valerio Massoli, Fabrizio Falchi, Alperen Kantarcı, Şeymanur Aktı, Hazim Kemal Ekenel, Giuseppe Amato

Indeed, differently from commonly used approaches that consider a neural network as a single computational block, i. e., using the output of the last layer only, MOCCA explicitly leverages the multi-layer structure of deep architectures.

Anomaly Detection Classification +1

Words as Art Materials: Generating Paintings with Sequential GANs

1 code implementation8 Jul 2020 Azmi Can Özgen, Hazim Kemal Ekenel

These variations in images provide originality which is an important factor for artistic essence.

Benefiting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution

no code implementations6 Jul 2020 Mohammad Saeed Rad, Thomas Yu, Claudiu Musat, Hazim Kemal Ekenel, Behzad Bozorgtabar, Jean-Philippe Thiran

First, we train a network to transform real LR images to the space of bicubically downsampled images in a supervised manner, by using both real LR/HR pairs and synthetic pairs.

Image Super-Resolution

Ear2Face: Deep Biometric Modality Mapping

1 code implementation2 Jun 2020 Dogucan Yaman, Fevziye Irem Eyiokur, Hazim Kemal Ekenel

We have achieved very promising results, especially on the FERET dataset, generating visually appealing face images from ear image inputs.

Image-to-Image Translation Person Identification

Offline Signature Verification on Real-World Documents

1 code implementation25 Apr 2020 Deniz Engin, Alperen Kantarcı, Seçil Arslan, Hazim Kemal Ekenel

Research on offline signature verification has explored a large variety of methods on multiple signature datasets, which are collected under controlled conditions.

Thermal to Visible Face Recognition Using Deep Autoencoders

1 code implementation10 Feb 2020 Alperen Kantarcı, Hazim Kemal Ekenel

Also, we assess the impact of alignment in thermal to visible face recognition.

Face Recognition

SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

no code implementations ICCV 2019 Mohammad Saeed Rad, Behzad Bozorgtabar, Urs-Viktor Marti, Max Basler, Hazim Kemal Ekenel, Jean-Philippe Thiran

By benefiting from perceptual losses, recent studies have improved significantly the performance of the super-resolution task, where a high-resolution image is resolved from its low-resolution counterpart.

Image Super-Resolution

Benefiting from Multitask Learning to Improve Single Image Super-Resolution

no code implementations29 Jul 2019 Mohammad Saeed Rad, Behzad Bozorgtabar, Claudiu Musat, Urs-Viktor Marti, Max Basler, Hazim Kemal Ekenel, Jean-Philippe Thiran

Despite significant progress toward super resolving more realistic images by deeper convolutional neural networks (CNNs), reconstructing fine and natural textures still remains a challenging problem.

Image Super-Resolution Semantic Segmentation

Multimodal Age and Gender Classification Using Ear and Profile Face Images

1 code implementation23 Jul 2019 Dogucan Yaman, Fevziye Irem Eyiokur, Hazim Kemal Ekenel

Experimental results indicated that profile face images contain a rich source of information for age and gender classification.

Age And Gender Classification Classification +3

Exploring Factors for Improving Low Resolution Face Recognition

no code implementations23 Jul 2019 Omid Abdollahi Aghdam, Behzad Bozorgtabar, Hazim Kemal Ekenel, Jean-Philippe Thiran

By leveraging this information, we have utilized deep face models trained on MS-Celeb-1M and fine-tuned on VGGFace2 dataset and achieved state-of-the-art accuracies on the SCFace and ICB-RW benchmarks, even without using any training data from the datasets of these benchmarks.

Face Recognition

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

2 code implementations27 May 2019 Guillaume Jaume, Hazim Kemal Ekenel, Jean-Philippe Thiran

We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms.

Optical Character Recognition

Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

no code implementations17 May 2019 Behzad Bozorgtabar, Mohammad Saeed Rad, Hazim Kemal Ekenel, Jean-Philippe Thiran

Moreover, we also conduct experiments on a near-infrared dataset containing facial expression videos of drivers to assess the performance using in-the-wild data for driver emotion recognition.

Domain Adaptation Emotion Recognition +2

Learn to synthesize and synthesize to learn

1 code implementation1 May 2019 Behzad Bozorgtabar, Mohammad Saeed Rad, Hazim Kemal Ekenel, Jean-Philippe Thiran

To overcome these shortcomings, we propose attribute guided face image generation method using a single model, which is capable to synthesize multiple photo-realistic face images conditioned on the attributes of interest.

Data Augmentation Facial Expression Recognition +2

The Unconstrained Ear Recognition Challenge 2019 - ArXiv Version With Appendix

no code implementations11 Mar 2019 Žiga Emeršič, Aruna Kumar S. V., B. S. Harish, Weronika Gutfeter, Jalil Nourmohammadi Khiarak, Andrzej Pacut, Earnest Hansley, Mauricio Pamplona Segundo, Sudeep Sarkar, Hyeonjung Park, Gi Pyo Nam, Ig-Jae Kim, Sagar G. Sangodkar, Ümit Kaçar, Murvet Kirci, Li Yuan, Jishou Yuan, Haonan Zhao, Fei Lu, Junying Mao, Xiaoshuang Zhang, Dogucan Yaman, Fevziye Irem Eyiokur, Kadir Bulut Özler, Hazim Kemal Ekenel, Debbrota Paul Chowdhury, Sambit Bakshi, Pankaj K. Sa, Banshidhar Majhi, Peter Peer, Vitomir Štruc

The goal of the challenge is to assess the performance of existing ear recognition techniques on a challenging large-scale ear dataset and to analyze performance of the technology from various viewpoints, such as generalization abilities to unseen data characteristics, sensitivity to rotations, occlusions and image resolution and performance bias on sub-groups of subjects, selected based on demographic criteria, i. e. gender and ethnicity.

Person Recognition

Age and Gender Classification From Ear Images

no code implementations14 Jun 2018 Dogucan Yaman, Fevziye Irem Eyiokur, Nurdan Sezgin, Hazim Kemal Ekenel

Although there have been a few previous work on gender classification using ear images, to the best of our knowledge, this study is the first work on age classification from ear images.

Age And Gender Classification Age Estimation +3

Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing

2 code implementations14 May 2018 Deniz Engin, Anıl Genç, Hazim Kemal Ekenel

In this paper, we present an end-to-end network, called Cycle-Dehaze, for single image dehazing problem, which does not require pairs of hazy and corresponding ground truth images for training.

Image Dehazing Single Image Dehazing

Domain Adaptation for Ear Recognition Using Deep Convolutional Neural Networks

1 code implementation21 Mar 2018 Fevziye Irem Eyiokur, Dogucan Yaman, Hazim Kemal Ekenel

We have first shown the importance of domain adaptation, when deep convolutional neural network models are used for ear recognition.

Domain Adaptation

Combining Multiple Views for Visual Speech Recognition

no code implementations19 Oct 2017 Marina Zimmermann, Mostafa Mehdipour Ghazi, Hazim Kemal Ekenel, Jean-Philippe Thiran

In this paper, we explore this aspect and provide a comprehensive study on combining multiple views for visual speech recognition.

Visual Speech Recognition

Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem GMM-HMM System

no code implementations19 Oct 2017 Marina Zimmermann, Mostafa Mehdipour Ghazi, Hazim Kemal Ekenel, Jean-Philippe Thiran

Automatic visual speech recognition is an interesting problem in pattern recognition especially when audio data is noisy or not readily available.

Visual Speech Recognition

Combining LiDAR Space Clustering and Convolutional Neural Networks for Pedestrian Detection

no code implementations17 Oct 2017 Damien Matti, Hazim Kemal Ekenel, Jean-Philippe Thiran

In purely image-based pedestrian detection approaches, the state-of-the-art results have been achieved with convolutional neural networks (CNN) and surprisingly few detection frameworks have been built upon multi-cue approaches.

Pedestrian Detection

Strengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations

1 code implementation4 Oct 2017 Klemen Grm, Vitomir Štruc, Anais Artiges, Matthieu Caron, Hazim Kemal Ekenel

However, studies systematically exploring the strengths and weaknesses of existing deep models for face recognition are still relatively scarce in the literature.

Face Recognition Face Verification

Exploiting Convolution Filter Patterns for Transfer Learning

no code implementations23 Aug 2017 Mehmet Aygün, Yusuf Aytar, Hazim Kemal Ekenel

In this paper, we introduce a new regularization technique for transfer learning.

Transfer Learning

Face Deidentification with Generative Deep Neural Networks

no code implementations28 Jul 2017 Blaž Meden, Refik Can Malli, Sebastjan Fabijan, Hazim Kemal Ekenel, Vitomir Štruc, Peter Peer

Our results show that the recognition performance on deidentified images is close to chance, suggesting that the deidentification process based on GNNs is highly effective.

How Transferable are CNN-based Features for Age and Gender Classification?

no code implementations1 Oct 2016 Gökhan Özbulak, Yusuf Aytar, Hazim Kemal Ekenel

Domain specific VGG-Face CNN model has been found to be more useful and provided better performance for both age and gender classification tasks, when compared with generic AlexNet-like model, which shows that transfering from a closer domain is more useful.

Age And Gender Classification Classification +2

How Image Degradations Affect Deep CNN-based Face Recognition?

no code implementations18 Aug 2016 Samil Karahan, Merve Kilinc Yildirim, Kadir Kirtac, Ferhat Sukru Rende, Gultekin Butun, Hazim Kemal Ekenel

This is particularly important, since in real-world face recognition applications, images may contain various kinds of degradations due to motion blur, noise, compression artifacts, color distortions, and occlusion.

Face Recognition

A Comprehensive Analysis of Deep Learning Based Representation for Face Recognition

no code implementations9 Jun 2016 Mostafa Mehdipour Ghazi, Hazim Kemal Ekenel

Deep learning based approaches have been dominating the face recognition field due to the significant performance improvement they have provided on the challenging wild datasets.

Face Recognition

Apparent Age Estimation Using Ensemble of Deep Learning Models

no code implementations9 Jun 2016 Refik Can Malli, Mehmet Aygun, Hazim Kemal Ekenel

To account for multiple labels per image, instead of using average age of the annotated face image as the class label, we have grouped the face images that are within a specified age range.

Age Estimation

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