Interactive Segmentation
29 papers with code • 12 benchmarks • 7 datasets
Libraries
Use these libraries to find Interactive Segmentation models and implementationsMost implemented papers
Reviving Iterative Training with Mask Guidance for Interactive Segmentation
We find that the models trained on a combination of COCO and LVIS with diverse and high-quality annotations show performance superior to all existing models.
Deep Interactive Object Selection
Interactive object selection is a very important research problem and has many applications.
f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation
We propose f-BRS (feature backpropagating refinement scheme) that solves an optimization problem with respect to auxiliary variables instead of the network inputs, and requires running forward and backward pass just for a small part of a network.
Getting to 99% Accuracy in Interactive Segmentation
We propose a novel interactive architecture and a novel training scheme that are both tailored to better exploit the user workflow.
EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow
In addition, with the proposed method, we develop an efficient interactive segmentation tool for practical data annotation tasks.
Deep Extreme Cut: From Extreme Points to Object Segmentation
This paper explores the use of extreme points in an object (left-most, right-most, top, bottom pixels) as input to obtain precise object segmentation for images and videos.
NuClick: A Deep Learning Framework for Interactive Segmentation of Microscopy Images
As nuclei, cells and glands are fundamental objects for downstream analysis in computational pathology/cytology, in this paper we propose a simple CNN-based approach to speed up collecting annotations for these objects which requires minimum interaction from the annotator.
Interactive Object Segmentation With Inside-Outside Guidance
This paper explores how to harvest precise object segmentation masks while minimizing the human interaction cost.
Interactive Image Segmentation With First Click Attention
In the task of interactive image segmentation, users initially click one point to segment the main body of the target object and then provide more points on mislabeled regions iteratively for a precise segmentation.
Medical Image Segmentation Using Deep Learning: A Survey
Firstly, compared to traditional surveys that directly divide literatures of deep learning on medical image segmentation into many groups and introduce literatures in detail for each group, we classify currently popular literatures according to a multi-level structure from coarse to fine.