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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 131–140 of 296 papers

TitleStatusHype
Exploiting Shape Cues for Weakly Supervised Semantic Segmentation—0
Learning Pseudo Labels for Semi-and-Weakly Supervised Semantic SegmentationCode0
LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes—0
eX-ViT: A Novel eXplainable Vision Transformer for Weakly Supervised Semantic Segmentation—0
Mining Discriminative Food Regions for Accurate Food RecognitionCode1
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic SegmentationCode0
Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology ImagesCode1
Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference—0
One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model—0
RecurSeed and EdgePredictMix: Pseudo-Label Refinement Learning for Weakly Supervised Semantic Segmentation across Single- and Multi-Stage FrameworksCode1
Show:102550
← PrevPage 14 of 30Next →

No leaderboard results yet.