Eva Cetinic

According to our database, Eva Cetinic authored at least 16 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Synthetic History: Evaluating Visual Representations of the Past in Diffusion Models.

Maria-Teresa De Rosa Palmini, Eva Cetinic

CoRR, May, 2025

Perpetuating Misogyny with Generative AI: How Model Personalization Normalizes Gendered Harm.

Laura Wagner, Eva Cetinic

CoRR, May, 2025

Exploring Language Patterns of Prompts in Text-to-Image Generation and Their Impact on Visual Diversity.

Maria-Teresa De Rosa Palmini, Eva Cetinic

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

2024

Patterns of Creativity: How User Input Shapes AI-Generated Visual Diversity.

Maria-Teresa De Rosa Palmini, Eva Cetinic

CoRR, 2024

Civiverse: A Dataset for Analyzing User Engagement with Open-Source Text-to-Image Models.

Maria-Teresa De Rosa Palmini, Laura Wagner, Eva Cetinic

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023

A Computational Approach to Hand Pose Recognition in Early Modern Paintings.

Valentine Bernasconi, Eva Cetinic, Leonardo Impett

J. Imaging, 2023

2022

Understanding and Creating Art with AI: Review and Outlook.

Eva Cetinic, James She

ACM Trans. Multim. Comput. Commun. Appl., 2022

The Myth of Culturally Agnostic AI Models.

Eva Cetinic

CoRR, 2022

2021

Towards Generating and Evaluating Iconographic Image Captions of Artworks.

Eva Cetinic

J. Imaging, 2021

2020

Learning the Principles of Art History with convolutional neural networks.

Eva Cetinic, Tomislav Lipic, Sonja Grgic

Pattern Recognit. Lett., 2020

Iconographic Image Captioning for Artworks.

Eva Cetinic

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

2019

Računalno otkrivanje stilskih obilježja slikarskih djela utemeljeno na analizi značajki slike više razine ; Computational detection of stylistic properties of paintings based on high-level image feature analysis.

Eva Cetinic

PhD thesis, 2019

A Deep Learning Perspective on Beauty, Sentiment, and Remembrance of Art.

Eva Cetinic, Tomislav Lipic, Sonja Grgic

IEEE Access, 2019

2018

INDIGO-DataCloud: a Platform to Facilitate Seamless Access to E-Infrastructures.

Davide Salomoni, Isabel Campos Plasencia, Luciano Gaido, Jesús E. Marco de Lucas, P. Solagna, Jorge Gomes, Ludek Matyska, P. Fuhrman, Marcus Hardt, Giacinto Donvito, Lukasz Dutka, Marcin Plóciennik, Roberto Barbera, Ignacio Blanquer, Andrea Ceccanti, Eva Cetinic, Mário David, Doina Cristina Duma, Álvaro López García, Germán Moltó, Pablo Orviz Fernández, Zdenek Sustr, Matthew Viljoen, Fernando Aguilar, Luís Alves, Marica Antonacci, Lucio Angelo Antonelli, Stefano Bagnasco, A. Bonving, Riccardo Bruno, Y. Chen, Alessandro Costa, Davor Davidovic, Benjamin Ertl, Marco Fargetta, Sandro Fiore, S. Gallozzi, Z. Kurkcuoglu, Lara Lloret Iglesias, J. Martins, Alessandra Nuzzo, Paola Nassisi, Cosimo Palazzo, João Murta Pina, Eva Sciacca, Daniele Spiga, Marco Antonio Tangaro, Michal Urbaniak, Sara Vallero, Bas Wegh, Valentina Zaccolo, Federico Zambelli, Tomasz Zok

J. Grid Comput., 2018

Fine-tuning Convolutional Neural Networks for fine art classification.

Eva Cetinic, Tomislav Lipic, Sonja Grgic

Expert Syst. Appl., 2018

How Convolutional Neural Networks Remember Art.

Eva Cetinic, Tomislav Lipic, Sonja Grgic

Proceedings of the 25th International Conference on Systems, Signals and Image Processing, 2018