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 151160 of 296 papers

TitleStatusHype
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic SegmentationCode0
Precision matters: Precision-aware ensemble for weakly supervised semantic segmentationCode0
PSDPM: Prototype-based Secondary Discriminative Pixels Mining for Weakly Supervised Semantic SegmentationCode0
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation ApproachCode0
Removing supervision in semantic segmentation with local-global matching and area balancingCode0
Rethinking Saliency-Guided Weakly-Supervised Semantic SegmentationCode0
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic SegmentationCode0
Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic SegmentationCode0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
Self-Supervised Difference Detection for Weakly-Supervised Semantic SegmentationCode0
Show:102550
← PrevPage 16 of 30Next →

No leaderboard results yet.