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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 1120 of 296 papers

TitleStatusHype
POT: Prototypical Optimal Transport for Weakly Supervised Semantic SegmentationCode1
MoRe: Class Patch Attention Needs Regularization for Weakly Supervised Semantic SegmentationCode1
Revisiting the Integration of Convolution and Attention for Vision BackboneCode1
EP-SAM: Weakly Supervised Histopathology Segmentation via Enhanced Prompt with Segment AnythingCode1
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event CamerasCode1
3D Weakly Supervised Semantic Segmentation with 2D Vision-Language GuidanceCode1
Knowledge Transfer with Simulated Inter-Image Erasing 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
Scribble Hides Class: Promoting Scribble-Based Weakly-Supervised Semantic Segmentation with Its Class LabelCode1
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