12 citations · 13 across the 12 of their papers we have counts for
12 papers
Learning visual representations for compositional analysis of artworks and photographs
Fatemeh Behrad, Tinne Tuytelaars, Johan Wagemans
Composition, the deliberate arrangement of visual elements, is central to how meaning, emotion, and aesthetic quality are conveyed in artwork, yet it remains among the least formal…
DODA: A Database of Datasets for Aesthetics Research
Lisa Koßmann, Ralf Bartho, Christoph Redies +1
With rapid growth in the fields of empirical and computational aesthetics we have seen a vast increase in large image datasets annotated for aesthetics. As the image databases diff…
Personalizing Text-to-Image Generation to Individual Taste
Anne-Sofie Maerten, Juliane Verwiebe, Shyamgopal Karthik +3
Modern text-to-image (T2I) models generate high-fidelity visuals but remain indifferent to individual user preferences. While existing reward models optimize for "average" human ap…
From Concepts to Judgments: Interpretable Image Aesthetic Assessment
Xiao-Chang Liu, Johan Wagemans
Image aesthetic assessment (IAA) aims to predict the aesthetic quality of images as perceived by humans. While recent IAA models achieve strong predictive performance, they offer l…
Charm: The Missing Piece in ViT fine-tuning for Image Aesthetic Assessment
Fatemeh Behrad, Tinne Tuytelaars, Johan Wagemans
The capacity of Vision transformers (ViTs) to handle variable-sized inputs is often constrained by computational complexity and batch processing limitations. Consequently, ViTs are…
LAPIS: A novel dataset for personalized image aesthetic assessment
Anne-Sofie Maerten, Li-Wei Chen, Stefanie De Winter +2
We present the Leuven Art Personalized Image Set (LAPIS), a novel dataset for personalized image aesthetic assessment (PIAA). It is the first dataset with images of artworks that i…
On the Role of Individual Differences in Current Approaches to Computational Image Aesthetics
Li-Wei Chen, Ombretta Strafforello, Anne-Sofie Maerten +2
Image aesthetic assessment (IAA) evaluates image aesthetics, a task complicated by image diversity and user subjectivity. Current approaches address this in two stages: Generic IAA…
Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks
Yuyan Zhang, Derya Soydaner, Fatemeh Behrad +2
Deep neural networks perform well in object recognition, but do they perceive objects like humans? This study investigates the Gestalt principle of closure in convolutional neural…
BackFlip: The Impact of Local and Global Data Augmentations on Artistic Image Aesthetic Assessment
Ombretta Strafforello, Gonzalo Muradas Odriozola, Fatemeh Behrad +4
Assessing the aesthetic quality of artistic images presents unique challenges due to the subjective nature of aesthetics and the complex visual characteristics inherent to artworks…
Finding Closure: A Closer Look at the Gestalt Law of Closure in Convolutional Neural Networks
Yuyan Zhang, Derya Soydaner, Lisa Koßmann +2
The human brain has an inherent ability to fill in gaps to perceive figures as complete wholes, even when parts are missing or fragmented. This phenomenon is known as Closure in ps…
A toolbox for calculating objective image properties in aesthetics research
Christoph Redies, Ralf Bartho, Lisa Koßmann +4
Over the past two decades, researchers in the field of visual aesthetics have studied numerous quantitative (objective) image properties and how they relate to visual aesthetic app…
Unveiling The Factors of Aesthetic Preferences with Explainable AI
Derya Soydaner, Johan Wagemans
The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspectiv…