SegAnimeChara: Segmenting Anime Characters Generated by AI

Abstract

This work introduces SegAnimeChara, a novel system of transforming AI-generated anime images into game characters while retaining unique features. Using volume-based body pose segmentation, SegAnimeChara can efficiently, zero-shot, segment body parts from generative images based on OpenPose human skeleton. Furthermore, this system integrates a semantic segmentation pipeline based on the text prompts of the existing Text2Image workflow. The system conserves the game character’s unique outfit and reduces the redundant duplicate text prompts for semantic segmentation.