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 121130 of 296 papers

TitleStatusHype
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic SegmentationCode0
Inferring the Class Conditional Response Map for Weakly Supervised Semantic SegmentationCode0
HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency RegularizationCode0
Removing supervision in semantic segmentation with local-global matching and area balancingCode0
HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide ImagesCode0
High-fidelity Pseudo-labels for Boosting Weakly-Supervised SegmentationCode0
Rethinking Saliency-Guided Weakly-Supervised Semantic SegmentationCode0
COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical imagesCode0
All-pairs Consistency Learning for Weakly Supervised Semantic SegmentationCode0
PSDPM: Prototype-based Secondary Discriminative Pixels Mining for Weakly Supervised Semantic SegmentationCode0
Show:102550
← PrevPage 13 of 30Next →

No leaderboard results yet.