ReMOVE: A Reference-free Metric for Object Erasure

Aditya Chandrasekar,Goirik Chakrabarty,Jai Bardhan,Ramya Hebbalaguppe,Prathosh AP; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024, pp. 7901-7910

We introduce ReMOVE a novel reference-free metric for assessing object erasure efficacy in diffusion-based image editing models post-generation. Unlike existing measures such as LPIPS and CLIPScore ReMOVE addresses the challenge of evaluating inpainting without a reference image common in practical scenarios. It effectively distinguishes between object removal and replacement. This is a key issue in diffusion models due to stochastic nature of image generation. Traditional metrics fail to align with the intuitive definition of inpainting which aims for (1) seamless object removal within masked regions (2) while preserving the background continuity. ReMOVE not only correlates with state-of-the-art metrics and aligns with human perception but also captures the nuanced aspects of the inpainting process providing a finer-grained evaluation of the generated outputs.