68 citations · 83 across the 14 of their papers we have counts for
18 papers
Shared Latent Representation for Joint Text-to-Audio-Visual Synthesis
Dogucan Yaman, Seymanur Akti, Fevziye Irem Eyiokur +1
We propose a text-to-talking-face synthesis framework leveraging latent speech representations from HierSpeech++. A Text-to-Vec module generates Wav2Vec2 embeddings from text, whic…
Assessing Identity Leakage in Talking Face Generation: Metrics and Evaluation Framework
Dogucan Yaman, Fevziye Irem Eyiokur, Hazım Kemal Ekenel +1
Video editing-based talking face generation aims to preserve video details such as pose, lighting, and gestures while modifying only lip motion, often using an identity reference i…
A Multimodal Depth-Aware Method For Embodied Reference Understanding
Fevziye Irem Eyiokur, Dogucan Yaman, Hazım Kemal Ekenel +1
Embodied Reference Understanding requires identifying a target object in a visual scene based on both language instructions and pointing cues. While prior works have shown progress…
Mask-Free Audio-driven Talking Face Generation for Enhanced Visual Quality and Identity Preservation
Dogucan Yaman, Fevziye Irem Eyiokur, Leonard Bärmann +2
Audio-Driven Talking Face Generation aims at generating realistic videos of talking faces, focusing on accurate audio-lip synchronization without deteriorating any identity-related…
CAPE: A CLIP-Aware Pointing Ensemble of Complementary Heatmap Cues for Embodied Reference Understanding
Fevziye Irem Eyiokur, Dogucan Yaman, Hazım Kemal Ekenel +1
We address Embodied Reference Understanding, the task of predicting the object a person in the scene refers to through pointing gesture and language. This requires multimodal reaso…
Titanic Calling: Low Bandwidth Video Conference from the Titanic Wreck
Fevziye Irem Eyiokur, Christian Huber, Thai-Binh Nguyen +5
In this paper, we report on communication experiments conducted in the summer of 2022 during a deep dive to the wreck of the Titanic. Radio transmission is not possible in deep sea…
Audio-Visual Speech Representation Expert for Enhanced Talking Face Video Generation and Evaluation
Dogucan Yaman, Fevziye Irem Eyiokur, Leonard Bärmann +3
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 inf…
Audio-driven Talking Face Generation with Stabilized Synchronization Loss
Dogucan Yaman, Fevziye Irem Eyiokur, Leonard Bärmann +2
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 a…
Face-Dubbing++: Lip-Synchronous, Voice Preserving Translation of Videos
Alexander Waibel, Moritz Behr, Fevziye Irem Eyiokur +7
In this paper, we propose a neural end-to-end system for voice preserving, lip-synchronous translation of videos. The system is designed to combine multiple component models and pr…
Exposure Correction Model to Enhance Image Quality
Fevziye Irem Eyiokur, Dogucan Yaman, Hazım Kemal Ekenel +1
Exposure errors in an image cause a degradation in the contrast and low visibility in the content. In this paper, we address this problem and propose an end-to-end exposure correct…
Alpha Matte Generation from Single Input for Portrait Matting
Dogucan Yaman, Hazım Kemal Ekenel, Alexander Waibel
In the portrait matting, the goal is to predict an alpha matte that identifies the effect of each pixel on the foreground subject. Traditional approaches and most of the existing w…
CAGAN: Text-To-Image Generation with Combined Attention GANs
Henning Schulze, Dogucan Yaman, Alexander Waibel
Generating images according to natural language descriptions is a challenging task. Prior research has mainly focused to enhance the quality of generation by investigating the use…
Ear2Face: Deep Biometric Modality Mapping
Dogucan Yaman, Fevziye Irem Eyiokur, Hazım Kemal Ekenel
In this paper, we explore the correlation between different visual biometric modalities. For this purpose, we present an end-to-end deep neural network model that learns a mapping…
Multimodal Age and Gender Classification Using Ear and Profile Face Images
Dogucan Yaman, Fevziye Irem Eyiokur, Hazım Kemal Ekenel
In this paper, we present multimodal deep neural network frameworks for age and gender classification, which take input a profile face image as well as an ear image. Our main objec…
The Unconstrained Ear Recognition Challenge 2019 - ArXiv Version With Appendix
Žiga Emeršič, Aruna Kumar S. V., B. S. Harish +28
This paper presents a summary of the 2019 Unconstrained Ear Recognition Challenge (UERC), the second in a series of group benchmarking efforts centered around the problem of person…
Age and Gender Classification From Ear Images
Dogucan Yaman, Fevziye Irem Eyiokur, Nurdan Sezgin +1
In this paper, we present a detailed analysis on extracting soft biometric traits, age and gender, from ear images. Although there have been a few previous work on gender classific…
Domain Adaptation for Ear Recognition Using Deep Convolutional Neural Networks
Fevziye Irem Eyiokur, Dogucan Yaman, Hazım Kemal Ekenel
In this paper, we have extensively investigated the unconstrained ear recognition problem. We have first shown the importance of domain adaptation, when deep convolutional neural n…
The Unconstrained Ear Recognition Challenge
Žiga Emeršič, Dejan Štepec, Vitomir Štruc +11
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 i…