Moonworks Lunara Aesthetic Dataset

TL;DR

The Moonworks Lunara Aesthetic Dataset is a high-quality, diverse collection of AI-generated images emphasizing aesthetic styles, detailed annotations, and licensing transparency, designed to advance aesthetic understanding in AI research.

Contribution

It introduces a novel dataset with superior aesthetic scores, diverse artistic styles, and detailed annotations, supporting research in aesthetic quality and style recognition.

Findings

Dataset exceeds existing aesthetic datasets in quality

Includes diverse regional artistic styles

Provides detailed annotations and licensing transparency

Abstract

The dataset spans diverse artistic styles, including regionally grounded aesthetics from the Middle East, Northern Europe, East Asia, and South Asia, alongside general categories such as sketch and oil painting. All images are generated using the Moonworks Lunara model and intentionally crafted to embody distinct, high-quality aesthetic styles, yielding a first-of-its-kind dataset with substantially higher aesthetic scores, exceeding even aesthetics-focused datasets, and general-purpose datasets by a larger margin. Each image is accompanied by a human-refined prompt and structured annotations that jointly describe salient objects, attributes, relationships, and stylistic cues. Unlike large-scale web-derived datasets that emphasize breadth over precision, the Lunara Aesthetic Dataset prioritizes aesthetic quality, stylistic diversity, and licensing transparency, and is released under the Apache 2.0 license to support research and unrestricted academic and commercial use.