8 citations · 11 across the 4 of their papers we have counts for
5 papers · 1 filter
NSYNC: Negative Synthetic Image Generation for Contrastive Training to Improve Stylized Text-To-Image Translation
Serkan Ozturk, Samet Hicsonmez, Pinar Duygulu
Current text conditioned image generation methods output realistic looking images, but they fail to capture specific styles. Simply finetuning them on the target style datasets sti…
A Deep Dive into Adversarial Robustness in Zero-Shot Learning
Mehmet Kerim Yucel, Ramazan Gokberk Cinbis, Pinar Duygulu
Machine learning (ML) systems have introduced significant advances in various fields, due to the introduction of highly complex models. Despite their success, it has been shown mul…
GANILLA: Generative Adversarial Networks for Image to Illustration Translation
Samet Hicsonmez, Nermin Samet, Emre Akbas +1
In this paper, we explore illustrations in children's books as a new domain in unpaired image-to-image translation. We show that although the current state-of-the-art image-to-imag…
Wildest Faces: Face Detection and Recognition in Violent Settings
Mehmet Kerim Yucel, Yunus Can Bilge, Oguzhan Oguz +3
With the introduction of large-scale datasets and deep learning models capable of learning complex representations, impressive advances have emerged in face detection and recogniti…
DRAW: Deep networks for Recognizing styles of Artists Who illustrate children's books
Samet Hicsonmez, Nermin Samet, Fadime Sener +1
This paper is motivated from a young boy's capability to recognize an illustrator's style in a totally different context. In the book "We are All Born Free" [1], composed of select…