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 161170 of 296 papers

TitleStatusHype
Self-supervised Scale Equivariant Network for Weakly Supervised Semantic SegmentationCode0
SPARS: Self-Play Adversarial Reinforcement Learning for Segmentation of Liver TumoursCode0
Spatio-temporal video autoencoder with differentiable memoryCode0
STC: A Simple to Complex Framework for Weakly-supervised Semantic SegmentationCode0
Tackling Ambiguity from Perspective of Uncertainty Inference and Affinity Diversification for Weakly Supervised Semantic SegmentationCode0
Towards Single Stage Weakly Supervised Semantic SegmentationCode0
Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image SegmentationCode0
Weakly Supervised Semantic Segmentation using Out-of-Distribution DataCode0
Weakly Supervised Semantic Segmentation via Progressive Patch LearningCode0
Weakly Supervised Semantic Segmentation via Progressive Confidence Region ExpansionCode0
Show:102550
← PrevPage 17 of 30Next →

No leaderboard results yet.