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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 161170 of 296 papers

TitleStatusHype
MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing dataCode1
Towards Noiseless Object Contours for Weakly Supervised Semantic Segmentation0
CLIMS: Cross Language Image Matching for Weakly Supervised Semantic Segmentation0
C-CAM: Causal CAM for Weakly Supervised Semantic Segmentation on Medical ImageCode0
MSG-SR-Net: A Weakly Supervised Network Integrating Multi-Scale Generation and Super-Pixel Refinement for Building Extraction from High-Resolution Remotely Sensed ImageriesCode0
Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching0
Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic SegmentationCode1
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic SegmentationCode1
Exploring Pixel-level Self-supervision for Weakly Supervised Semantic Segmentation0
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentationCode1
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