Illustrious: an Open Advanced Illustration Model
Authors: name: Sang Hyun Park, name: Jun Young Koh, name: Junha Lee, name: Joy Song, name: Dongha Kim, name: Hoyeon Moon, name: Hyunju Lee, name: Min Song

In this work, we share the insights for achieving state-of-the-art quality in
our text-to-image anime image generative model, called Illustrious. To achieve
high resolution, dynamic color range images, and high restoration ability, we
focus on three critical approaches for model improvement. First, we delve into
the significance of the batch size and dropout control, which enables faster
learning of controllable token based concept activations. Second, we increase
the training resolution of images, affecting the accurate depiction of
character anatomy in much higher resolution, extending its generation
capability over 20MP with proper methods. Finally, we propose the refined
multi-level captions, covering all tags and various natural language captions
as a critical factor for model development. Through extensive analysis and
experiments, Illustrious demonstrates state-of-the-art performance in terms of
animation style, outperforming widely-used models in illustration domains,
propelling easier customization and personalization with nature of open source.
We plan to publicly release updated Illustrious model series sequentially as
well as sustainable plans for improvements.