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 281–290 of 296 papers

TitleStatusHype
Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation—0
Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network—0
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach—0
Weakly Supervised Semantic Segmentation using Web-Crawled Videos—0
Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation—0
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation—0
Weakly-Supervised Semantic Segmentation using Motion Cues—0
Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation—0
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network—0
Semantic Component Analysis—0
Show:102550
← PrevPage 29 of 30Next →

No leaderboard results yet.