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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 131–140 of 296 papers

TitleStatusHype
CoBra: Complementary Branch Fusing Class and Semantic Knowledge for Robust Weakly Supervised Semantic Segmentation—0
Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation—0
Gated CRF Loss for Weakly Supervised Semantic Image Segmentation—0
3D Guided Weakly Supervised Semantic Segmentation—0
Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues—0
Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation—0
Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference—0
Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization—0
Attention Bridging Network for Knowledge Transfer—0
From Image-level to Pixel-level Labeling with Convolutional Networks—0
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