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20162026
most citedStrengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations

217 citations · 875 across the 53 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

Facial Attribute Based Text Guided Face Anonymization

Mustafa İzzet Muştu, Hazım Kemal Ekenel

The increasing prevalence of computer vision applications necessitates handling vast amounts of visual data, often containing personal information. While this technology offers sig…

cs.CV2025

Assessing the Use of Face Swapping Methods as Face Anonymizers in Videos

Mustafa İzzet Muştu, Hazım Kemal Ekenel

The increasing demand for large-scale visual data, coupled with strict privacy regulations, has driven research into anonymization methods that hide personal identities without ser…

cs.CV2025

A Survey on Class-Agnostic Counting: Advancements from Reference-Based to Open-World Text-Guided Approaches

Luca Ciampi, Ali Azmoudeh, Elif Ecem Akbaba +5

Visual object counting has recently shifted towards class-agnostic counting (CAC), which addresses the challenge of counting objects across arbitrary categories, a crucial capabili…