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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 6170 of 296 papers

TitleStatusHype
Weakly Supervised Semantic Segmentation for Driving ScenesCode1
TagCLIP: A Local-to-Global Framework to Enhance Open-Vocabulary Multi-Label Classification of CLIP Without TrainingCode1
Progressive Feature Self-reinforcement for Weakly Supervised Semantic SegmentationCode1
Densify Your Labels: Unsupervised Clustering with Bipartite Matching for Weakly Supervised Point Cloud Segmentation0
Foundation Model Assisted Weakly Supervised Semantic SegmentationCode1
Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation ModelsCode0
Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation0
Top-K Pooling with Patch Contrastive Learning for Weakly-Supervised Semantic Segmentation0
Dual-Augmented Transformer Network for Weakly Supervised Semantic Segmentation0
COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation0
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