Image Aesthetic Assessment

Image aesthetic assessment (IAA) focuses on automatically determining the perceived beauty or artistic merit of images, a complex task due to the subjective nature of aesthetics. Current research emphasizes leveraging multi-modal data (images and text), employing advanced architectures like graph attention networks and learnable queries within pre-trained models (e.g., CLIP) to extract relevant features, and exploring self-supervised learning techniques to address data scarcity issues, particularly in niche areas like children's art. These advancements improve the accuracy and efficiency of IAA, with implications for applications ranging from content recommendation systems to automated art evaluation and educational tools.