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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 201210 of 296 papers

TitleStatusHype
PointMatch: A Consistency Training Framework for Weakly Supervised Semantic Segmentation of 3D Point Clouds0
Weakly-Supervised Semantic Segmentation with Visual Words Learning and Hybrid PoolingCode0
Weakly Supervised Semantic Segmentation of Remote Sensing Images for Tree Species Classification Based on Explanation Methods0
MuSCLe: A Multi-Strategy Contrastive Learning Framework for Weakly Supervised Semantic Segmentation0
Towards Noiseless Object Contours for Weakly Supervised Semantic Segmentation0
C-CAM: Causal CAM for Weakly Supervised Semantic Segmentation on Medical ImageCode0
CLIMS: Cross Language Image Matching for Weakly Supervised Semantic Segmentation0
MSG-SR-Net: A Weakly Supervised Network Integrating Multi-Scale Generation and Super-Pixel Refinement for Building Extraction from High-Resolution Remotely Sensed ImageriesCode0
Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching0
Exploring Pixel-level Self-supervision for Weakly Supervised Semantic Segmentation0
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