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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 8190 of 296 papers

TitleStatusHype
Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic SegmentationCode1
Affinity Attention Graph Neural Network for Weakly Supervised Semantic SegmentationCode1
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic SegmentationCode1
Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive LearningCode1
SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point CloudsCode1
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic SegmentationCode1
Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional NetworksCode1
Non-Salient Region Object Mining for Weakly Supervised Semantic SegmentationCode1
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance SegmentationCode1
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic SegmentationCode1
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