Quantifying Likeness: A Computer Vision Approach to Identifying Style and Copyright Infringement in AI-Generated Artwork

This study proposes a computer vision approach to quantify stylistic similarity and potential copyright infringement in AI-generated artwork. The authors develop a small, customizable model that artists can use to assess if an AI-generated work infringes on their style, focusing on animators, surface designers, and digital artists as key stakeholders. Using techniques like saliency mapping and feature visualization, the model provides interpretable similarity scores to support expert analysis. While not intended to replace legal judgment, this framework aims to contribute to clearer guidelines for evaluating copyright infringement in AI-generated content by making concepts like "substantial similarity" more quantifiable and explicit.