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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 251260 of 296 papers

TitleStatusHype
Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation0
Gated CRF Loss for Weakly Supervised Semantic Image Segmentation0
Movable-Object-Aware Visual SLAM via Weakly Supervised Semantic Segmentation0
Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation0
Harvesting Information from Captions for Weakly Supervised Semantic Segmentation0
Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic SegmentationCode0
Weakly Supervised Semantic Segmentation of Satellite Images0
Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues0
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference0
The effect of scene context on weakly supervised semantic segmentation0
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