SOTAVerified

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

Showing 101110 of 296 papers

TitleStatusHype
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic SegmentationCode1
Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic SegmentationCode1
Token Contrast for Weakly-Supervised Semantic SegmentationCode1
Multi-class Token Transformer for Weakly Supervised Semantic SegmentationCode1
Unlocking the Potential of Ordinary Classifier: Class-Specific Adversarial Erasing Framework for Weakly Supervised Semantic SegmentationCode1
MoRe: Class Patch Attention Needs Regularization for Weakly Supervised Semantic SegmentationCode1
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentationCode1
Group-Wise Learning for Weakly Supervised Semantic SegmentationCode1
Group-Wise Semantic Mining for Weakly Supervised Semantic SegmentationCode1
Weakly Supervised Semantic Segmentation with Boundary ExplorationCode1
Show:102550
← PrevPage 11 of 30Next →

No leaderboard results yet.