CFR-ICL: Cascade-Forward Refinement with Iterative Click Loss for Interactive Image Segmentation

arXiv:2303.05620v2 Announce Type: replace
Abstract: The click-based interactive segmentation aims to extract the object of interest from an image with the guidance of user clicks. Recent work has achieved great overall performance by employing feedback from the output. However, in most state-of-the-art approaches, 1) the inference stage involves inflexible heuristic rules and requires a separate refinement model, and 2) the number of user clicks and model performance cannot be balanced. To address the challenges, we propose a click-based and mask-guided …

abstract art arxiv click cs.cv extract feedback guidance image inference interactive iterative loss object performance segmentation stage state type work