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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 226–250 of 296 papers

TitleStatusHype
Small Objects Matters in Weakly-supervised Semantic Segmentation—0
Weakly-supervised Semantic Segmentation via Dual-stream Contrastive Learning of Cross-image Contextual Information—0
COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation—0
WegFormer: Transformers for Weakly Supervised Semantic Segmentation—0
Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation—0
CoBra: Complementary Branch Fusing Class and Semantic Knowledge for Robust Weakly Supervised Semantic Segmentation—0
SSA: Semantic Structure Aware Inference for Weakly Pixel-Wise Dense Predictions without Cost—0
A Weakly-Supervised Semantic Segmentation Approach based on the Centroid Loss: Application to Quality Control and Inspection—0
Superpixel Boundary Correction for Weakly-Supervised Semantic Segmentation on Histopathology Images—0
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma—0
Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation—0
The effect of scene context on weakly supervised semantic segmentation—0
CLIMS: Cross Language Image Matching for Weakly Supervised Semantic Segmentation—0
CG-fusion CAM: Online segmentation of laser-induced damage on large-aperture optics—0
ToNNO: Tomographic Reconstruction of a Neural Network's Output for Weakly Supervised Segmentation of 3D Medical Images—0
Top-K Pooling with Patch Contrastive Learning for Weakly-Supervised Semantic Segmentation—0
Toward Modality Gap: Vision Prototype Learning for Weakly-supervised Semantic Segmentation with CLIP—0
Towards Closing the Gap in Weakly Supervised Semantic Segmentation with DCNNs: Combining Local and Global Models—0
Towards Noiseless Object Contours for Weakly Supervised Semantic Segmentation—0
Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels—0
Causal Intervention for Weakly-Supervised Semantic Segmentation—0
Treating Pseudo-labels Generation as Image Matting for Weakly Supervised Semantic Segmentation—0
Two-Phase Learning for Weakly Supervised Object Localization—0
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation—0
Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation—0
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