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Weakly supervised segmentation

Papers

Showing 126147 of 147 papers

TitleStatusHype
DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task InteractionsCode0
Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classificationCode0
PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical InstrumentsCode0
Integral Object Mining via Online Attention AccumulationCode0
Weakly supervised segmentation of intracranial aneurysms using a novel 3D focal modulation UNetCode0
Constrained Convolutional Neural Networks for Weakly Supervised SegmentationCode0
Constrained-CNN losses for weakly supervised segmentationCode0
Robustness and Overfitting Behavior of Implicit Background ModelsCode0
High-fidelity Pseudo-labels for Boosting Weakly-Supervised SegmentationCode0
Collaborative Propagation on Multiple Instance Graphs for 3D Instance Segmentation with Single-point SupervisionCode0
Competing for pixels: a self-play algorithm for weakly-supervised segmentationCode0
Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide imagesCode0
CaCL: Class-aware Codebook Learning for Weakly Supervised Segmentation on Diffuse Image PatternsCode0
HELPNet: Hierarchical Perturbations Consistency and Entropy-guided Ensemble for Scribble Supervised Medical Image SegmentationCode0
Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational modelCode0
A Baseline Statistical Method For Robust User-Assisted Multiple SegmentationCode0
CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic SegmentationCode0
Self-Supervised Difference Detection for Weakly-Supervised Semantic SegmentationCode0
Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation LearningCode0
Floor Plan Image Segmentation Via Scribble-Based Semi-Weakly Supervised Learning: A Style and Category-Agnostic ApproachCode0
SESS: Saliency Enhancing with Scaling and SlidingCode0
ACCL: Adversarial constrained-CNN loss for weakly supervised medical image segmentationCode0
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