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Few-Shot Semantic Segmentation
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Few-shot semantic segmentation (FSS) learns to segment target objects in query image given few pixel-wise annotated support image.
논문
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Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain
Domain-Rectifying Adapter for Cross-Domain Few-Shot Segmentation
LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation
A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models
Boosting Few-Shot Semantic Segmentation Via Segment Anything Model
Analyzing Local Representations of Self-supervised Vision Transformers
Relevant Intrinsic Feature Enhancement Network for Few-Shot Semantic Segmentation
Background Clustering Pre-training for Few-shot Segmentation
Language-guided Few-shot Semantic Segmentation
Self-guided Few-shot Semantic Segmentation for Remote Sensing Imagery Based on Large Vision Models
Target-aware Bi-Transformer for Few-shot Segmentation
Masked Cross-image Encoding for Few-shot Segmentation
Self-Calibrated Cross Attention Network for Few-Shot Segmentation
Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond
Prototypical Kernel Learning and Open-set Foreground Perception for Generalized Few-shot Semantic Segmentation
Self-supervised Few-shot Learning for Semantic Segmentation: An Annotation-free Approach
Dense Affinity Matching for Few-Shot Segmentation
DifFSS: Diffusion Model for Few-Shot Semantic Segmentation
Hierarchical Dense Correlation Distillation for Few-Shot Segmentation-Extended Abstract
Unsupervised augmentation optimization for few-shot medical image segmentation
Reflection Invariance Learning for Few-shot Semantic Segmentation
MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation
Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation
Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation
Clustered-patch Element Connection for Few-shot Learning
[CLS] Token is All You Need for Zero-Shot Semantic Segmentation
Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges
ForamViT-GAN: Exploring New Paradigms in Deep Learning for Micropaleontological Image Analysis
SegGPT: Segmenting Everything In Context
Hierarchical Dense Correlation Distillation for Few-Shot Segmentation
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation
Iterative Few-shot Semantic Segmentation from Image Label Text
A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation
Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving
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