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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 281–290 of 296 papers

TitleStatusHype
Information Entropy Based Feature Pooling for Convolutional Neural Networks—0
Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation—0
Mitigating Undisciplined Over-Smoothing in Transformer 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
Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation—0
Image Augmentation Agent for Weakly Supervised Semantic Segmentation—0
Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image—0
Movable-Object-Aware Visual SLAM via Weakly Supervised Semantic Segmentation—0
Weakly Supervised Semantic Segmentation of Remote Sensing Images for Tree Species Classification Based on Explanation Methods—0
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