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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 51–75 of 296 papers

TitleStatusHype
ISIM: Iterative Self-Improved Model for Weakly Supervised SegmentationCode1
Extracting Class Activation Maps from Non-Discriminative Features as wellCode1
Multi-Layer Pseudo-Supervision for Histopathology Tissue Semantic Segmentation using Patch-level Classification LabelsCode1
Non-Salient Region Object Mining for Weakly Supervised Semantic SegmentationCode1
Background Activation Suppression for Weakly Supervised Object Localization and Semantic SegmentationCode1
Complementary Patch for Weakly Supervised Semantic SegmentationCode1
Conditional Diffusion Models for Weakly Supervised Medical Image SegmentationCode1
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic SegmentationCode1
Context Decoupling Augmentation for Weakly Supervised Semantic SegmentationCode1
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic SegmentationCode1
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance SegmentationCode1
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-RefinementCode1
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentationCode1
EP-SAM: Weakly Supervised Histopathology Segmentation via Enhanced Prompt with Segment AnythingCode1
An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation ProblemsCode1
Group-Wise Learning for Weakly Supervised Semantic SegmentationCode1
Knowledge Transfer with Simulated Inter-Image Erasing for Weakly Supervised Semantic SegmentationCode1
DHR: Dual Features-Driven Hierarchical Rebalancing in Inter- and Intra-Class Regions for Weakly-Supervised Semantic SegmentationCode1
Group-Wise Semantic Mining for Weakly Supervised Semantic SegmentationCode1
Hierarchical Semantic Contrast for Weakly Supervised Semantic SegmentationCode1
Discriminative Region Suppression for Weakly-Supervised Semantic SegmentationCode1
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic SegmentationCode1
Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic SegmentationCode1
Dual Progressive Transformations for Weakly Supervised Semantic SegmentationCode1
Modeling the Background for Incremental and Weakly-Supervised Semantic SegmentationCode1
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