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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 221–230 of 296 papers

TitleStatusHype
Weakly Supervised Semantic Segmentation of Remote Sensing Images for Tree Species Classification Based on Explanation Methods—0
Weakly-Supervised Semantic Segmentation of Ships Using Thermal Imagery—0
Weakly-Supervised Semantic Segmentation of Circular-Scan, Synthetic-Aperture-Sonar Imagery—0
Weakly Supervised Semantic Segmentation of Echocardiography Videos via Multi-level Features Selection—0
Weakly-Supervised Semantic Segmentation using Motion Cues—0
Weakly Supervised Semantic Segmentation using Web-Crawled Videos—0
Weakly Supervised Semantic Segmentation Using Constrained Dominant Sets—0
Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching—0
Weakly-supervised Semantic Segmentation via Dual-stream Contrastive Learning of Cross-image Contextual Information—0
Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary—0
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