no code implementations • 7 May 2024 • Dogucan Yaman, Fevziye Irem Eyiokur, Leonard Bärmann, Seymanur Aktı, Hazim Kemal Ekenel, Alexander Waibel
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.
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 • 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 • 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 • 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.
no code implementations • 26 Apr 2021 • Henning Schulze, Dogucan Yaman, Alexander Waibel
Generating images according to natural language descriptions is a challenging task.
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 • 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.
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 • 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.
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 • 23 Aug 2017 • Žiga Emeršič, Dejan Štepec, Vitomir Štruc, Peter Peer, Anjith George, Adil Ahmad, Elshibani Omar, Terrance E. Boult, Reza Safdari, Yuxiang Zhou, Stefanos Zafeiriou, Dogucan Yaman, Fevziye I. Eyiokur, Hazim K. Ekenel
In this paper we present the results of the Unconstrained Ear Recognition Challenge (UERC), a group benchmarking effort centered around the problem of person recognition from ear images captured in uncontrolled conditions.