Comparing Interactive Image Segmentation Models under Different Clicking Procedures
Franco Marchesoni-Acland
⚠ This is a preprint. It may change before it is accepted for publication.


Interactive image segmentation (IIS) methods are usually evaluated in terms of segmentation performance vs. number of clicks (NoC). However, the automatic evaluation depends on a clicking procedure and its relation to the procedure used for training. In this work we compare qualitatively and quantitatively two state-of-the-art IIS methods that report the best performances but have not been compared against each other. We show i) what method is better, ii) that the performance is sensitive to clicking procedures, iii) what method is more robust to clicking procedures, and iv) that training with a specific clicking procedure does not guarantee the best performance using it.

This is an MLBriefs article, the source code has not been reviewed!
The original source code is available here (last checked 2023/09/12).