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 6170 of 296 papers

TitleStatusHype
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-RefinementCode1
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event CamerasCode1
Discriminative Region Suppression for Weakly-Supervised Semantic SegmentationCode1
An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation ProblemsCode1
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic SegmentationCode1
EP-SAM: Weakly Supervised Histopathology Segmentation via Enhanced Prompt with Segment AnythingCode1
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentationCode1
DHR: Dual Features-Driven Hierarchical Rebalancing in Inter- and Intra-Class Regions for Weakly-Supervised Semantic SegmentationCode1
Hunting Attributes: Context Prototype-Aware Learning for Weakly Supervised Semantic SegmentationCode1
MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing dataCode1
Show:102550
← PrevPage 7 of 30Next →

No leaderboard results yet.