mlsanityData to 14 Oct 2026

One-Shot Instance Segmentation

arXiv 1811.11507 ↗First posted 28 Nov 2018cs.CVcited by 43

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Abstract (arXiv)

We tackle the problem of one-shot instance segmentation: Given an example image of a novel, previously unknown object category, find and segment all objects of this category within a complex scene. To address this challenging new task, we propose Siamese Mask R-CNN. It extends Mask R-CNN by a Siamese backbone encoding both reference image and scene, allowing it to target detection and segmentation towards the reference category. We demonstrate empirical results on MS Coco highlighting challenges of the one-shot setting: while transferring knowledge about instance segmentation to novel object categories works very well, targeting the detection network towards the reference category appears to be more difficult. Our work provides a first strong baseline for one-shot instance segmentation and will hopefully inspire further research into more powerful and flexible scene analysis algorithms. Code is available at: https://github.com/bethgelab/siamese-mask-rcnn

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Nov 2018.

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Citing papers per year: 2021: 9; 2022: 12; 2023: 11; 2024: 7; 2025: 2; 2026: 2.

43 papers.

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  1. 2021Image Segmentation Using Text and Image Promptscited by 512
  2. 2022Simple Open-Vocabulary Object Detection with Vision Transformerscited by 305
  3. 2023Towards Open Vocabulary Learning: A Surveycited by 166
  4. 2022A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunitiescited by 163
  5. 2021Generalized Few-Shot Object Detection without Forgettingcited by 88
  6. 2022Learning from Few Examples: A Summary of Approaches to Few-Shot Learningcited by 86
  7. 2022OSOP: A Multi-Stage One Shot Object Pose Estimation Frameworkcited by 81
  8. 2021Incremental Few-Shot Instance Segmentationcited by 49
  9. 2022Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervisioncited by 41
  10. 2022One-Shot Transfer of Affordance Regions? AffCorrs!cited by 31
  11. 2021Few-Shot Object Detection: A Comprehensive Surveycited by 29
  12. 2023Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matchingcited by 29
31 more
  1. 2023Single-Stage Visual Query Localization in Egocentric Videoscited by 20
  2. 2022iFS-RCNN: An Incremental Few-shot Instance Segmentercited by 19
  3. 2023MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentationcited by 18
  4. 2023Can SAM Count Anything? An Empirical Study on SAM Countingcited by 18
  5. 2021FAPIS: A Few-shot Anchor-free Part-based Instance Segmentercited by 15
  6. 2023Detect Everything with Few Examplescited by 14
  7. 2021Object Counting: You Only Need to Look at Onecited by 13
  8. 2023Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentationcited by 12
  9. 2022VizWiz-FewShot: Locating Objects in Images Taken by People With Visual Impairmentscited by 11
  10. 2022Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparisoncited by 8
  11. 2023UniAP: Towards Universal Animal Perception in Vision via Few-shot Learningcited by 7
  12. 2021A Survey of Deep Learning for Low-Shot Object Detectioncited by 6
  13. 2023Instance-level Few-shot Learning with Class Hierarchy Miningcited by 5
  14. 2024Few-shot Online Anomaly Detection and Segmentationcited by 5
  15. 2024BIV-Priv-Seg: Locating Private Content in Images Taken by People With Visual Impairmentscited by 5
  16. 2024Unsupervised Pre-training with Language-Vision Prompts for Low-Data Instance Segmentationcited by 4
  17. 2021CAT: Cross-Attention Transformer for One-Shot Object Detectioncited by 3
  18. 2021Localizing Infinity-shaped fishes: Sketch-guided object localization in the wildcited by 3
  19. 2022Geodesic-Former: a Geodesic-Guided Few-shot 3D Point Cloud Instance Segmentercited by 3
  20. 2023ENInst: Enhancing Weakly-supervised Low-shot Instance Segmentationcited by 2
  21. 2024UniFS: Universal Few-shot Instance Perception with Point Representationscited by 2
  22. 2024Learning Gaussian Data Augmentation in Feature Space for One-shot Object Detection in Mangacited by 2
  23. 2025Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentationcited by 1
  24. 2022Less than Few: Self-Shot Video Instance Segmentationcited by 0
  25. 2022Expanding continual few-shot learning benchmarks to include recognition of specific instancescited by 0
  26. 2023SKU-Patch: Towards Efficient Instance Segmentation for Unseen Objects in Auto-Storecited by 0
  27. 2024Deep ContourFlow: Advancing Active Contours with Deep Learningcited by 0
  28. 2024UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentationcited by 0
  29. 2025Indirect Attention: Turning Context Misalignment into a Featurecited by 0
  30. 2026From Pixels to Concepts: Do Segmentation Models Understand What They Segment?cited by 0
  31. 2026Boundary-by-Mask: Few-Shot Instance Segmentation with Mask-Conditioned Boundary Learning for Texture-Poor Industrial Partscited by 0