1 code implementation • 27 Apr 2024 • Ziya Ata Yazıcı, İlkay Öksüz, Hazim Kemal Ekenel
Notably, GLIMS achieved this high performance with a significantly reduced number of trainable parameters.
1 code implementation • 15 Mar 2024 • Ziya Ata Yazıcı, İlkay Öksüz, Hazim Kemal Ekenel
In our approach, we utilized a multi-scale, attention-guided and hybrid U-Net-shaped model -- GLIMS -- to perform 3D brain tumor segmentation in three regions: Enhancing Tumor (ET), Tumor Core (TC), and Whole Tumor (WT).
no code implementations • 1 Feb 2024 • Ziya Ata Yazıcı, Sara Colantonio, Hazim Kemal Ekenel
Human pose estimation, the process of identifying joint positions in a person's body from images or videos, represents a widely utilized technology across diverse fields, including healthcare.
no code implementations • 18 Jul 2023 • Dogucan Yaman, Fevziye Irem Eyiokur, Leonard Bärmann, Hazim Kemal Ekenel, Alexander Waibel
Specifically, this involves unintended flow of lip, pose and other information from the reference to the generated image, as well as instabilities during model training.
no code implementations • 28 Nov 2022 • Klemen Grm, Berk Kemal Özata, Vitomir Štruc, Hazim Kemal Ekenel
In this paper, we aim to address the large domain gap between high-resolution face images, e. g., from professional portrait photography, and low-quality surveillance images, e. g., from security cameras.
no code implementations • 7 Nov 2022 • Fevziye Irem Eyiokur, Alperen Kantarcı, Mustafa Ekrem Erakin, Naser Damer, Ferda Ofli, Muhammad Imran, Janez Križaj, Albert Ali Salah, Alexander Waibel, Vitomir Štruc, Hazim Kemal Ekenel
The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals.
1 code implementation • 2 Nov 2022 • Alperen Kantarcı, Ferda Ofli, Muhammad Imran, Hazim Kemal Ekenel
In this work, we present a novel face mask detection dataset that contains images posted on Twitter during the pandemic from around the world.
1 code implementation • 4 Aug 2022 • Pedro C. Neto, Fadi Boutros, Joao Ribeiro Pinto, Naser Damer, Ana F. Sequeira, Jaime S. Cardoso, Messaoud Bengherabi, Abderaouf Bousnat, Sana Boucheta, Nesrine Hebbadj, Mustafa Ekrem Erakin, Uğur Demir, Hazim Kemal Ekenel, Pedro Beber de Queiroz Vidal, David Menotti
This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022).
no code implementations • 26 Jun 2022 • Slavisa Aleksic, Michael Atanasov, Jean Calleja Agius, Kenneth Camilleri, Anto Cartolovni, Pau Climent-Peerez, Sara Colantonio, Stefania Cristina, Vladimir Despotovic, Hazim Kemal Ekenel, Ekrem Erakin, Francisco Florez-Revuelta, Danila Germanese, Nicole Grech, Steinunn Gróa Sigurðardóttir, Murat Emirzeoglu, Ivo Iliev, Mladjan Jovanovic, Martin Kampel, William Kearns, Andrzej Klimczuk, Lambros Lambrinos, Jennifer Lumetzberger, Wiktor Mucha, Sophie Noiret, Zada Pajalic, Rodrigo Rodriguez Peerez, Galidiya Petrova, Sintija Petrovica, Peter Pocta, Angelica Poli, Mara Pudane, Susanna Spinsante, Albert Ali Salah, Maria Jose Santofimia, Anna Sigridur Islind, Lacramioara Stoicu-Tivadar, Hilda Tellioglu, Andrej Zgank
The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation.
no code implementations • 9 Jun 2022 • Alexander Waibel, Moritz Behr, Fevziye Irem Eyiokur, Dogucan Yaman, Tuan-Nam Nguyen, Carlos Mullov, Mehmet Arif Demirtas, Alperen Kantarcı, Stefan Constantin, Hazim Kemal Ekenel
The system is designed to combine multiple component models and produces a video of the original speaker speaking in the target language that is lip-synchronous with the target speech, yet maintains emphases in speech, voice characteristics, face video of the original speaker.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +6
1 code implementation • 26 May 2022 • Duygu Sesver, Alp Eren Gençoğlu, Çağrı Emre Yıldız, Zehra Günindi, Faeze Habibi, Ziya Ata Yazıcı, Hazim Kemal Ekenel
To assess the performance of the recent state-of-the-art approaches, Vision Transformer and TimeSformer, as well as to explore the contribution of video-based information for incident classification, we performed benchmark experiments on the VIDI and Incidents Dataset.
1 code implementation • 22 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.
no code implementations • 20 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.
1 code implementation • 16 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.
1 code implementation • 8 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.
no code implementations • 8 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.
no code implementations • 6 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.
2 code implementations • 16 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.
1 code implementation • 9 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.
Ranked #80 on Anomaly Detection on MVTec AD
1 code implementation • 8 Jul 2020 • Azmi Can Özgen, Hazim Kemal Ekenel
These variations in images provide originality which is an important factor for artistic essence.
no code implementations • 6 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.
1 code implementation • 2 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.
1 code implementation • 25 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.
1 code implementation • 11 Feb 2020 • Şeymanur Aktı, Gözde Ayşe Tataroğlu, Hazim Kemal Ekenel
This dataset is made publicly available.
1 code implementation • 10 Feb 2020 • Alperen Kantarcı, Hazim Kemal Ekenel
Also, we assess the impact of alignment in thermal to visible face recognition.
Ranked #1 on Face Recognition on Carl
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.
no code implementations • 29 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.
no code implementations • 23 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.
1 code implementation • 23 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.
3 code implementations • 27 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 Optical Character Recognition (OCR) +1
no code implementations • 17 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.
1 code implementation • 1 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.
no code implementations • 11 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.
no code implementations • 9 Nov 2018 • Guillaume Jaume, Behzad Bozorgtabar, Hazim Kemal Ekenel, Jean-Philippe Thiran, Maria Gabrani
We introduce a new scene graph generation method called image-level attentional context modeling (ILAC).
no code implementations • 14 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.
3 code implementations • 14 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.
Ranked #4 on Image Dehazing on O-Haze
1 code implementation • 21 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.
no code implementations • 31 Oct 2017 • Mohammad Saeed Rad, Andreas von Kaenel, Andre Droux, Francois Tieche, Nabil Ouerhani, Hazim Kemal Ekenel, Jean-Philippe Thiran
Littering quantification is an important step for improving cleanliness of cities.
no code implementations • 19 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.
no code implementations • 19 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.
no code implementations • 17 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.
1 code implementation • 4 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.
no code implementations • 23 Aug 2017 • Mehmet Aygün, Yusuf Aytar, Hazim Kemal Ekenel
In this paper, we introduce a new regularization technique for transfer learning.
no code implementations • 28 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.
no code implementations • 1 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.
no code implementations • 18 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.
no code implementations • 9 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.
no code implementations • 9 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.