Zobrazeno 1 - 10
of 139
pro vyhledávání: '"Ekenel, Hazım Kemal"'
Autor:
Sarıtaş, Erdi, Ekenel, Hazım Kemal
Advancements like Generative Adversarial Networks have attracted the attention of researchers toward face image synthesis to generate ever more realistic images. Thereby, the need for the evaluation criteria to assess the realism of the generated ima
Externí odkaz:
http://arxiv.org/abs/2406.02153
Autor:
Sarıtaş, Erdi, Ekenel, Hazım Kemal
A face recognition model is typically trained on large datasets of images that may be collected from controlled environments. This results in performance discrepancies when applied to real-world scenarios due to the domain gap between clean and in-th
Externí odkaz:
http://arxiv.org/abs/2406.02142
Autor:
Yaman, Dogucan, Eyiokur, Fevziye Irem, Bärmann, Leonard, Aktı, Seymanur, Ekenel, Hazım Kemal, Waibel, Alexander
In the task of talking face generation, the objective is to generate a face video with lips synchronized to the corresponding audio while preserving visual details and identity information. Current methods face the challenge of learning accurate lip
Externí odkaz:
http://arxiv.org/abs/2405.04327
Convolutional Neural Networks (CNNs) have become widely adopted for medical image segmentation tasks, demonstrating promising performance. However, the inherent inductive biases in convolutional architectures limit their ability to model long-range d
Externí odkaz:
http://arxiv.org/abs/2404.17854
Glioblastoma is a highly aggressive and malignant brain tumor type that requires early diagnosis and prompt intervention. Due to its heterogeneity in appearance, developing automated detection approaches is challenging. To address this challenge, Art
Externí odkaz:
http://arxiv.org/abs/2403.09942
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. One such healthcare application involves in-bed pose esti
Externí odkaz:
http://arxiv.org/abs/2402.00700
Autor:
Yaman, Dogucan, Eyiokur, Fevziye Irem, Bärmann, Leonard, Ekenel, Hazim Kemal, Waibel, Alexander
Talking face generation aims to create realistic videos with accurate lip synchronization and high visual quality, using given audio and reference video while preserving identity and visual characteristics. In this paper, we start by identifying seve
Externí odkaz:
http://arxiv.org/abs/2307.09368
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. Establishing an identity match between disparat
Externí odkaz:
http://arxiv.org/abs/2211.15225
Autor:
Eyiokur, Fevziye Irem, Kantarcı, Alperen, Erakın, Mustafa Ekrem, Damer, Naser, Ofli, Ferda, Imran, Muhammad, Križaj, Janez, Salah, Albert Ali, Waibel, Alexander, Štruc, Vitomir, Ekenel, Hazım Kemal
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. Various prevention measures were introduced around the world to limit the transmission of the disease, including fac
Externí odkaz:
http://arxiv.org/abs/2211.03705
In December 2019, a novel coronavirus (COVID-19) spread so quickly around the world that many countries had to set mandatory face mask rules in public areas to reduce the transmission of the virus. To monitor public adherence, researchers aimed to ra
Externí odkaz:
http://arxiv.org/abs/2211.01207