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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 51–100 of 296 papers

TitleStatusHype
Semantic Prompt Learning for Weakly-Supervised Semantic SegmentationCode1
Spatial Structure Constraints for Weakly Supervised Semantic SegmentationCode1
Weakly-Supervised Semantic Segmentation of Circular-Scan, Synthetic-Aperture-Sonar Imagery—0
P2Seg: Pointly-supervised Segmentation via Mutual Distillation—0
Question-Answer Cross Language Image Matching for Weakly Supervised Semantic SegmentationCode1
Clustering-Guided Class Activation for Weakly Supervised Semantic SegmentationCode0
PSDPM: Prototype-based Secondary Discriminative Pixels Mining for Weakly Supervised Semantic SegmentationCode0
From SAM to CAMs: Exploring Segment Anything Model for Weakly Supervised Semantic SegmentationCode2
Class Tokens Infusion for Weakly Supervised Semantic SegmentationCode1
PointCT: Point Central Transformer Network for Weakly-supervised Point Cloud Semantic SegmentationCode1
Weakly Supervised Semantic Segmentation for Driving ScenesCode1
TagCLIP: A Local-to-Global Framework to Enhance Open-Vocabulary Multi-Label Classification of CLIP Without TrainingCode1
Progressive Feature Self-reinforcement for Weakly Supervised Semantic SegmentationCode1
Densify Your Labels: Unsupervised Clustering with Bipartite Matching for Weakly Supervised Point Cloud Segmentation—0
Foundation Model Assisted Weakly Supervised Semantic SegmentationCode1
Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation ModelsCode0
Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation—0
Top-K Pooling with Patch Contrastive Learning for Weakly-Supervised Semantic Segmentation—0
Dual-Augmented Transformer Network for Weakly Supervised Semantic Segmentation—0
COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation—0
Weakly Supervised Semantic Segmentation by Knowledge Graph InferenceCode1
Small Objects Matters in Weakly-supervised Semantic Segmentation—0
Background Activation Suppression for Weakly Supervised Object Localization and Semantic SegmentationCode1
From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion ModelsCode0
BroadCAM: Outcome-agnostic Class Activation Mapping for Small-scale Weakly Supervised ApplicationsCode0
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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