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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

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Showing 161–170 of 296 papers

TitleStatusHype
Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image—0
Image Augmentation Agent for Weakly Supervised Semantic Segmentation—0
Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation—0
Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation—0
Information Entropy Based Feature Pooling for Convolutional Neural Networks—0
LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes—0
Learning Multi-Modal Class-Specific Tokens for Weakly Supervised Dense Object Localization—0
Learning random-walk label propagation for weakly-supervised semantic segmentation—0
Learning Segmentation Masks with the Independence Prior—0
Learning to Detour: Shortcut Mitigating Augmentation for Weakly Supervised Semantic Segmentation—0
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