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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 7180 of 296 papers

TitleStatusHype
Weakly Supervised Semantic Segmentation by Knowledge Graph InferenceCode1
Small Objects Matters in Weakly-supervised Semantic Segmentation0
Background Activation Suppression for Weakly Supervised Object Localization and Semantic SegmentationCode1
From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion ModelsCode0
BroadCAM: Outcome-agnostic Class Activation Mapping for Small-scale Weakly Supervised ApplicationsCode0
Exploring Limits of Diffusion-Synthetic Training with Weakly Supervised Semantic Segmentation0
Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation0
CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images0
Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation0
All-pairs Consistency Learning for Weakly Supervised Semantic SegmentationCode0
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