2024/04/24 by Kuan-I Chung, Chung, Kuan-I, Daniel Moyer +1
Psychology · #Computer Vision and Pattern Recognition (cs.CV) #Educational Games and Gamification #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG)
paper · pdf · doi:10.48550/arxiv.2404.16155
openalex publication_date 2024/04/24 · openalex created_date 2024/04/27 · openalex updated_date 2026/07/28
We introduce an assessment procedure for interactive segmentation models. Based on concepts from Bayesian Experimental Design, the procedure measures a model's understanding of point prompts and their correspondence with the desired segmentation mask. We show that Oracle Dice index measurements are insensitive or even misleading in measuring this property. We demonstrate the use of the proposed procedure on three interactive segmentation models and subsets of two large image segmentation datasets.