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 2130 of 296 papers

TitleStatusHype
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event CamerasCode1
Adaptive Patch Contrast for Weakly Supervised Semantic Segmentation0
3D Weakly Supervised Semantic Segmentation with 2D Vision-Language GuidanceCode1
Knowledge Transfer with Simulated Inter-Image Erasing for Weakly Supervised Semantic SegmentationCode1
Precision matters: Precision-aware ensemble for weakly supervised semantic segmentationCode0
Fine-grained Background Representation for Weakly Supervised Semantic SegmentationCode0
Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic SegmentationCode2
Learning to Detour: Shortcut Mitigating Augmentation for Weakly Supervised Semantic Segmentation0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
Enhancing Weakly Supervised Semantic Segmentation with Multi-modal Foundation Models: An End-to-End Approach0
Show:102550
← PrevPage 3 of 30Next →

No leaderboard results yet.