Advancing Generative Model Evaluation: A Novel Algorithm for Realistic Image Synthesis and Comparison in OCR System

arXiv:2402.17204v1 Announce Type: new
Abstract: This research addresses a critical challenge in the field of generative models, particularly in the generation and evaluation of synthetic images. Given the inherent complexity of generative models and the absence of a standardized procedure for their comparison, our study introduces a pioneering algorithm to objectively assess the realism of synthetic images. This approach significantly enhances the evaluation methodology by refining the Fr\'echet Inception Distance (FID) score, allowing for a more precise and subjective assessment …

abstract algorithm arxiv challenge comparison complexity cs.cv evaluation generative generative models image images novel ocr research synthesis synthetic type