mlsanityData to 14 Oct 2026

One-Shot Learning for Semantic Segmentation

arXiv 1709.03410 ↗First posted 11 Sep 2017cs.CVcited by 337

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Abstract (arXiv)

Low-shot learning methods for image classification support learning from sparse data. We extend these techniques to support dense semantic image segmentation. Specifically, we train a network that, given a small set of annotated images, produces parameters for a Fully Convolutional Network (FCN). We use this FCN to perform dense pixel-level prediction on a test image for the new semantic class. Our architecture shows a 25% relative meanIoU improvement compared to the best baseline methods for one-shot segmentation on unseen classes in the PASCAL VOC 2012 dataset and is at least 3 times faster.

Key facts. Cited by 337 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Sep 2017.

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Citing papers per year: 2021: 59; 2022: 63; 2023: 70; 2024: 67; 2025: 54; 2026: 24.

337 papers.

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  1. 2022Language-driven Semantic Segmentationcited by 717
  2. 2021Image Segmentation Using Text and Image Promptscited by 512
  3. 2022Visual Prompting via Image Inpaintingcited by 250
  4. 2021Adaptive Prototype Learning and Allocation for Few-Shot Segmentationcited by 207
  5. 2021Hypercorrelation Squeeze for Few-Shot Segmentationcited by 193
  6. 2022A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunitiescited by 163
  7. 2023What Makes Good Examples for Visual In-Context Learning?cited by 150
  8. 2023Matcher: Segment Anything with One Shot Using All-Purpose Feature Matchingcited by 142
  9. 2021Few-Shot Segmentation via Cycle-Consistent Transformercited by 133
  10. 2022Learning What Not to Segment: A New Perspective on Few-Shot Segmentationcited by 120
  11. 2021Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformercited by 116
  12. 2022Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentationcited by 114
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  1. 2022Self-Support Few-Shot Semantic Segmentationcited by 96
  2. 2021Self-Guided and Cross-Guided Learning for Few-Shot Segmentationcited by 92
  3. 2021Repurposing GANs for One-shot Semantic Part Segmentationcited by 88
  4. 2023Hierarchical Dense Correlation Distillation for Few-Shot Segmentationcited by 84
  5. 2021MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Imagescited by 78
  6. 2023Review of Large Vision Models and Visual Prompt Engineeringcited by 77
  7. 2024VRP-SAM: SAM with Visual Reference Promptcited by 75
  8. 2021Mining Latent Classes for Few-shot Segmentationcited by 69
  9. 2022Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentationcited by 65
  10. 2021Recurrent Mask Refinement for Few-Shot Medical Image Segmentationcited by 63
  11. 2022Feature-Proxy Transformer for Few-Shot Segmentationcited by 58
  12. 2021A Closer Look at Self-training for Zero-Label Semantic Segmentationcited by 57
  13. 2022Learning Non-target Knowledge for Few-shot Semantic Segmentationcited by 57
  14. 2023Learning Mask-aware CLIP Representations for Zero-Shot Segmentationcited by 57
  15. 2021Learning Meta-class Memory for Few-Shot Semantic Segmentationcited by 56
  16. 2021Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Typescited by 54
  17. 2021Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentationcited by 53
  18. 2022Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuningcited by 50
  19. 2023A Survey on Few-Shot Class-Incremental Learningcited by 48
  20. 2023One-Shot Open Affordance Learning with Foundation Modelscited by 45
  21. 2022Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentationcited by 43
  22. 2023Exploring Effective Factors for Improving Visual In-Context Learningcited by 43
  23. 2022Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxelscited by 42
  24. 2025BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster responsecited by 41
  25. 2021One-Shot Object Affordance Detection in the Wildcited by 40
  26. 2022Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentationcited by 37
  27. 2021Few-shot Segmentation with Optimal Transport Matching and Message Flowcited by 36
  28. 2024Bridge the Points: Graph-based Few-shot Segment Anything Semanticallycited by 35
  29. 2022Few-shot Medical Image Segmentation with Cycle-resemblance Attentioncited by 33
  30. 2021One-Shot Affordance Detectioncited by 32
  31. 2023Self-Calibrated Cross Attention Network for Few-Shot Segmentationcited by 32
  32. 2021PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior Maskcited by 31
  33. 2021Novel Class Discovery in Semantic Segmentationcited by 31
  34. 2022One-Shot Transfer of Affordance Regions? AffCorrs!cited by 31
  35. 2023Instruct Me More! Random Prompting for Visual In-Context Learningcited by 30
  36. 2024Cross-Domain Few-Shot Segmentation via Iterative Support-Query Correspondence Miningcited by 30
  37. 2023Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matchingcited by 29
  38. 2022Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentationcited by 28

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