Generalized Few-Shot Semantic Segmentation
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Benchmarks
COCO-20i (1-shot)
PASCAL-5i (5-Shot)
COCO-20i (5-shot)
PASCAL-5i (1-Shot)
Most implemented
A Strong Baseline for Generalized Few-Shot Semantic Segmentation
Enhancing Generalized Few-Shot Semantic Segmentation via Effective Knowledge Transfer
A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation
Generalized Few-Shot Semantic Segmentation in Remote Sensing: Challenge and Benchmark
Applying ViT in Generalized Few-shot Semantic Segmentation
Papers
Training-Free Generalized Few-Shot Segmentation through Open-Vocabulary Semantic Arbitration
Generalized Few-Shot Semantic Segmentation (GFSS) has traditionally been approached as a representation-learning problem, requiring task-specific adaptation to incorporate novel classes from limited support examples. Rec…
Generalized Few-Shot Semantic SegmentationMake It Up: Fake Images, Real Gains in Generalized Few-shot Semantic Segmentation
Generalized few-shot semantic segmentation (GFSS) is fundamentally limited by the coverage of novel-class appearances under scarce annotations. While diffusion models can synthesize novel-class images at scale, practical…
Generalized Few-Shot Semantic SegmentationEnhancing Generalized Few-Shot Semantic Segmentation via Effective Knowledge Transfer
Generalized few-shot semantic segmentation (GFSS) aims to segment objects of both base and novel classes, using sufficient samples of base classes and few samples of novel classes. Representative GFSS approaches typicall…
Classifier calibrationFew-Shot Semantic SegmentationGeneralized Few-Shot Semantic SegmentationSemantic Segmentation+1A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation
The goal of generalized few-shot semantic segmentation (GFSS) is to recognize novel-class objects through training with a few annotated examples and the base-class model that learned the knowledge about the base classes.…
Few-Shot Semantic SegmentationGeneralized Few-Shot Semantic SegmentationInductive LearningSegmentation+1Generalized Few-Shot Semantic Segmentation in Remote Sensing: Challenge and Benchmark
Learning with limited labelled data is a challenging problem in various applications, including remote sensing. Few-shot semantic segmentation is one approach that can encourage deep learning models to learn from few lab…
Few-Shot Semantic SegmentationGeneralized Few-Shot Semantic SegmentationSegmentationSemantic SegmentationApplying ViT in Generalized Few-shot Semantic Segmentation
This paper explores the capability of ViT-based models under the generalized few-shot semantic segmentation (GFSS) framework. We conduct experiments with various combinations of backbone models, including ResNets and pre…
DecoderFew-Shot Semantic SegmentationGeneralized Few-Shot Semantic SegmentationSegmentation+1