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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 251–275 of 296 papers

TitleStatusHype
Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation—0
Harvesting Information from Captions for Weakly Supervised Semantic Segmentation—0
Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic SegmentationCode0
Weakly Supervised Learning of Instance Segmentation with Inter-pixel RelationsCode1
Weakly Supervised Semantic Segmentation of Satellite Images—0
Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues—0
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference—0
The effect of scene context on weakly supervised semantic segmentation—0
CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic SegmentationCode0
Learning Segmentation Masks with the Independence Prior—0
Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation—0
Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation—0
Weakly- and Semi-Supervised Panoptic SegmentationCode1
Towards Closing the Gap in Weakly Supervised Semantic Segmentation with DCNNs: Combining Local and Global Models—0
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic SegmentationCode0
Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features—0
Bootstrapping the Performance of Webly Supervised Semantic SegmentationCode0
Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region GrowingCode0
Constrained-CNN losses for weakly supervised segmentationCode0
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic SegmentationCode0
Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic SegmentationCode1
Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation—0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Learning random-walk label propagation 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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