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 261–270 of 296 papers

TitleStatusHype
CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic SegmentationCode0
Learning Segmentation Masks with the Independence Prior—0
Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation—0
Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation—0
Towards Closing the Gap in Weakly Supervised Semantic Segmentation with DCNNs: Combining Local and Global Models—0
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic SegmentationCode0
Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features—0
Bootstrapping the Performance of Webly Supervised Semantic SegmentationCode0
Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region GrowingCode0
Constrained-CNN losses for weakly supervised segmentationCode0
Show:102550
← PrevPage 27 of 30Next →

No leaderboard results yet.