PseudoClick: Interactive Image Segmentation with Click Imitation
The goal of click-based interactive image segmentation is to obtain precise object segmentation masks with limited user interaction, i.e., by a minimal number of user clicks. Existing methods require users to provide all the clicks: by first inspecting the segmentation mask and then providing points on mislabeled regions, iteratively. We ask the question: can our model directly predict where to click, so as to further reduce the user interaction cost? To this end, we propose {\PseudoClick}, a generic framework that enables existing segmentation networks to propose candidate next clicks. These automatically generated clicks, termed pseudo clicks in this work, serve as an imitation of human clicks to refine the segmentation mask.
Code (0)
등록된 구현이 없습니다.
Tasks
Image SegmentationSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
Clore: Interactive Pathology Image Segmentation with Click-based Local Refinement
Recent advancements in deep learning-based interactive segmentation methods have significantly improved pathology image segmentation. Most existing approaches utilize user-provided positive and negative clicks to guide t…
Interactive SegmentationImage SegmentationSAMSA: Segment Anything Model Enhanced with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
Hyperspectral imaging (HSI) provides rich spectral information for medical imaging, yet encounters significant challenges due to data limitations and hardware variations. We introduce SAMSA, a novel interactive segmentat…
Medical Image SegmentationInteractive SegmentationZero-Shot LearningDeep learning-based interactive segmentation in remote sensing
Interactive segmentation, a computer vision technique where a user provides guidance to help an algorithm segment a feature of interest in an image, has achieved outstanding accuracy and efficient human-computer interact…
Deep LearningInteractive SegmentationLand Cover ClassificationSegmentation+1Clicks2Line: Using Lines for Interactive Image Segmentation
For click-based interactive segmentation methods, reducing the number of clicks required to obtain a desired segmentation result is essential. Although recent click-based methods yield decent segmentation results, we obs…
Image SegmentationInteractive SegmentationSegmentationSemantic SegmentationRClicks: Realistic Click Simulation for Benchmarking Interactive Segmentation
The emergence of Segment Anything (SAM) sparked research interest in the field of interactive segmentation, especially in the context of image editing tasks and speeding up data annotation. Unlike common semantic segment…
BenchmarkingInteractive SegmentationSegmentationSemantic Segmentation