mlsanityData to 7 Oct 2026

Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation

arXiv 2210.06780 ↗First posted 13 Oct 2022cs.CVcited by 37

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Abstract (arXiv)

Few-shot semantic segmentation aims to segment the target objects in query under the condition of a few annotated support images. Most previous works strive to mine more effective category information from the support to match with the corresponding objects in query. However, they all ignored the category information gap between query and support images. If the objects in them show large intra-class diversity, forcibly migrating the category information from the support to the query is ineffective. To solve this problem, we are the first to introduce an intermediate prototype for mining both deterministic category information from the support and adaptive category knowledge from the query. Specifically, we design an Intermediate Prototype Mining Transformer (IPMT) to learn the prototype in an iterative way. In each IPMT layer, we propagate the object information in both support and query features to the prototype and then use it to activate the query feature map. By conducting this process iteratively, both the intermediate prototype and the query feature can be progressively improved. At last, the final query feature is used to yield precise segmentation prediction. Extensive experiments on both PASCAL-5i and COCO-20i datasets clearly verify the effectiveness of our IPMT and show that it outperforms previous state-of-the-art methods by a large margin. Code is available at https://github.com/LIUYUANWEI98/IPMT

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). Builds on 35 of its 56 references that are in the map. First posted on arXiv 13 Oct 2022.

Builds on

35 of 56 references.

References · 35

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  4. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  5. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  6. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  7. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  8. 2020End-to-End Object Detection with Transformerscited by 7,384
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  10. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,410
  11. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  12. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
23 more
  1. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,960
  2. 2020Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformerscited by 1,368
  3. 2019PANet: Few-Shot Image Semantic Segmentation with Prototype Alignmentcited by 449
  4. 2020TransTrack: Multiple Object Tracking with Transformercited by 370
  5. 2020MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformerscited by 355
  6. 2017One-Shot Learning for Semantic Segmentationcited by 337
  7. 2020Prior Guided Feature Enrichment Network for Few-Shot Segmentationcited by 271
  8. 2019CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learningcited by 217
  9. 2021Adaptive Prototype Learning and Allocation for Few-Shot Segmentationcited by 207
  10. 2021Hypercorrelation Squeeze for Few-Shot Segmentationcited by 193
  11. 2020Prototype Mixture Models for Few-shot Semantic Segmentationcited by 190
  12. 2019Feature Weighting and Boosting for Few-Shot Segmentationcited by 189
  13. 2020Part-aware Prototype Network for Few-shot Semantic Segmentationcited by 162
  14. 2020Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?cited by 135
  15. 2021Few-Shot Segmentation via Cycle-Consistent Transformercited by 133
  16. 2021Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformercited by 116
  17. 2020CRNet: Cross-Reference Networks for Few-Shot Segmentationcited by 101
  18. 2021Self-Guided and Cross-Guided Learning for Few-Shot Segmentationcited by 92
  19. 2022Learning Non-target Knowledge for Few-shot Semantic Segmentationcited by 57
  20. 2021Learning Meta-class Memory for Few-Shot Semantic Segmentationcited by 56
  21. 2021SOTR: Segmenting Objects with Transformerscited by 42
  22. 2022Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentationcited by 28
  23. 2021Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentationcited by 23

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 16; 2024: 9; 2025: 7; 2026: 3.

37 papers.

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  1. 2024Bridge the Points: Graph-based Few-shot Segment Anything Semanticallycited by 35
  2. 2023Self-Calibrated Cross Attention Network for Few-Shot Segmentationcited by 32
  3. 2023MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentationcited by 25
  4. 2022A Strong Baseline for Generalized Few-Shot Semantic Segmentationcited by 22
  5. 2023Multi-Modal Prototypes for Open-World Semantic Segmentationcited by 22
  6. 2023A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Applicationcited by 21
  7. 2023Few Shot Medical Image Segmentation with Cross Attention Transformercited by 19
  8. 2025DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistencycited by 15
  9. 2023Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentationcited by 13
  10. 2023Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentationcited by 12
  11. 2024Query-guided Prototype Evolution Network for Few-Shot Segmentationcited by 12
  12. 2024Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentationcited by 10
25 more
  1. 2024Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Promptscited by 9
  2. 2026COMBINER: Composed Image Retrieval Guided by Attribute-based Neighbor Relationscited by 9
  3. 2023Few-Shot Rotation-Invariant Aerial Image Semantic Segmentationcited by 7
  4. 2023Prototype-based Cross-Modal Object Trackingcited by 7
  5. 2022Prototype as Query for Few Shot Semantic Segmentationcited by 6
  6. 2024RobustEMD: Domain Robust Matching for Cross-domain Few-shot Medical Image Segmentationcited by 6
  7. 2025DSV-LFS: Unifying LLM-Driven Semantic Cues with Visual Features for Robust Few-Shot Segmentationcited by 6
  8. 2023[CLS] Token is All You Need for Zero-Shot Semantic Segmentationcited by 5
  9. 2023Dense Affinity Matching for Few-Shot Segmentationcited by 5
  10. 2024CONDA: Condensed Deep Association Learning for Co-Salient Object Detectioncited by 4
  11. 2023Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentationcited by 3
  12. 2023Disentangled Representation Learning with Transmitted Information Bottleneckcited by 3
  13. 2024Group-On: Boosting One-Shot Segmentation with Supportive Querycited by 3
  14. 2026Revealing the Semantic Selection Gap in DINOv3 through Training-Free Few-Shot Segmentationcited by 3
  15. 2023Holistic Prototype Attention Network for Few-Shot VOScited by 1
  16. 2024AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic Segmentationcited by 1
  17. 2025ProMi: An Efficient Prototype-Mixture Baseline for Few-Shot Segmentation with Bounding-Box Annotationscited by 1
  18. 2025ViRefSAM: Visual Reference-Guided Segment Anything Model for Remote Sensing Segmentationcited by 1
  19. 2025Unbiased Semantic Decoding with Vision Foundation Models for Few-shot Segmentationcited by 1
  20. 2023Target-aware Bi-Transformer for Few-shot Segmentationcited by 0
  21. 2023Reflection Invariance Learning for Few-shot Semantic Segmentationcited by 0
  22. 2024Applying ViT in Generalized Few-shot Semantic Segmentationcited by 0
  23. 2025LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentationcited by 0
  24. 2025Cross-Domain Few-Shot Segmentation via Ordinary Differential Equations over Time Intervalscited by 0
  25. 2026Training-Free Generalized Few-Shot Segmentation through Open-Vocabulary Semantic Arbitrationcited by 0