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Weakly-Supervised Semantic Segmentation

The semantic segmentation task is to assign a label from a label set to each pixel in an image. In the case of fully supervised setting, the dataset consists of images and their corresponding pixel-level class-specific annotations (expensive pixel-level annotations). However, in the weakly-supervised setting, the dataset consists of images and corresponding annotations that are relatively easy to obtain, such as tags/labels of objects present in the image.

( Image credit: Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing )

Papers

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Showing 76–100 of 296 papers

TitleStatusHype
Exploring Limits of Diffusion-Synthetic Training with Weakly Supervised Semantic Segmentation—0
Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation—0
CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images—0
Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation—0
All-pairs Consistency Learning for Weakly Supervised Semantic SegmentationCode0
MCTformer+: Multi-Class Token Transformer for Weakly Supervised Semantic SegmentationCode1
Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise—0
Hierarchical Semantic Contrast for Weakly Supervised Semantic SegmentationCode1
CG-fusion CAM: Online segmentation of laser-induced damage on large-aperture optics—0
Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic SegmentationCode1
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain TumorCode1
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor SegmentationCode0
Conditional Diffusion Models for Weakly Supervised Medical Image SegmentationCode1
P-NOC: adversarial training of CAM generating networks for robust weakly supervised semantic segmentation priors—0
Masked Collaborative Contrast for Weakly Supervised Semantic SegmentationCode0
A Self-Training Framework Based on Multi-Scale Attention Fusion for Weakly Supervised Semantic SegmentationCode0
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic SegmentationCode0
Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic SegmentationCode1
Mitigating Undisciplined Over-Smoothing in Transformer for Weakly Supervised Semantic Segmentation—0
Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation—0
An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation ProblemsCode1
MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic SegmentationCode1
Coupling Global Context and Local Contents for Weakly-Supervised Semantic SegmentationCode0
High-fidelity Pseudo-labels for Boosting Weakly-Supervised SegmentationCode0
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic SegmentationCode1
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