mlsanityData to 7 Oct 2026

DifFSS: Diffusion Model for Few-Shot Semantic Segmentation

arXiv 2307.00773 ↗First posted 3 Jul 2023cs.CV cs.AIcited by 22

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Diffusion models have demonstrated excellent performance in image generation. Although various few-shot semantic segmentation (FSS) models with different network structures have been proposed, performance improvement has reached a bottleneck. This paper presents the first work to leverage the diffusion model for FSS task, called DifFSS. DifFSS, a novel FSS paradigm, can further improve the performance of the state-of-the-art FSS models by a large margin without modifying their network structure. Specifically, we utilize the powerful generation ability of diffusion models to generate diverse auxiliary support images by using the semantic mask, scribble or soft HED boundary of the support image as control conditions. This generation process simulates the variety within the class of the query image, such as color, texture variation, lighting, etc. As a result, FSS models can refer to more diverse support images, yielding more robust representations, thereby achieving a consistent improvement in segmentation performance. Extensive experiments on three publicly available datasets based on existing advanced FSS models demonstrate the effectiveness of the diffusion model for FSS task. Furthermore, we explore in detail the impact of different input settings of the diffusion model on segmentation performance. Hopefully, this completely new paradigm will bring inspiration to the study of FSS task integrated with AI-generated content. Code is available at https://github.com/TrinitialChan/DifFSS

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 34 of its 38 references that are in the map. First posted on arXiv 3 Jul 2023.

Builds on

34 of 38 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021Label-Efficient Semantic Segmentation with Diffusion Models6 Dec

Other references · 33

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  5. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  6. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  7. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  8. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  9. 2017Prototypical Networks for Few-shot Learningcited by 3,001
  10. 2018Unified Perceptual Parsing for Scene Understandingcited by 1,265
  11. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  12. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,155
21 more
  1. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  2. 2015Holistically-Nested Edge Detectioncited by 590
  3. 2017One-Shot Learning for Semantic Segmentationcited by 337
  4. 2020Prior Guided Feature Enrichment Network for Few-Shot Segmentationcited by 271
  5. 2019CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learningcited by 217
  6. 2021Adaptive Prototype Learning and Allocation for Few-Shot Segmentationcited by 207
  7. 2021Hypercorrelation Squeeze for Few-Shot Segmentationcited by 193
  8. 2020Prototype Mixture Models for Few-shot Semantic Segmentationcited by 190
  9. 2019Feature Weighting and Boosting for Few-Shot Segmentationcited by 189
  10. 2018SG-One: Similarity Guidance Network for One-Shot Semantic Segmentationcited by 169
  11. 2020Part-aware Prototype Network for Few-shot Semantic Segmentationcited by 162
  12. 2019FSS-1000: A 1000-Class Dataset for Few-Shot Segmentationcited by 160
  13. 2021Few-Shot Segmentation via Cycle-Consistent Transformercited by 133
  14. 2022Learning What Not to Segment: A New Perspective on Few-Shot Segmentationcited by 120
  15. 2020CRNet: Cross-Reference Networks for Few-Shot Segmentationcited by 101
  16. 2023Hierarchical Dense Correlation Distillation for Few-Shot Segmentationcited by 84
  17. 2022Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentationcited by 65
  18. 2022Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Modelscited by 63
  19. 2021Score-Based Generative Classifierscited by 53
  20. 2020HoughNet: Integrating near and long-range evidence for bottom-up object detectioncited by 20
  21. 2021A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentationcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 14; 2025: 4; 2026: 1.

22 papers.

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  1. 2024SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentationcited by 41
  2. 2023Interpretable Diffusion via Information Decompositioncited by 37
  3. 2024Image Segmentation in Foundation Model Era: A Surveycited by 35
  4. 20233DiffTection: 3D Object Detection with Geometry-Aware Diffusion Featurescited by 26
  5. 2024Distillation of Diffusion Features for Semantic Correspondencecited by 17
  6. 2024Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentationcited by 16
  7. 2023AI-Generated Images as Data Source: The Dawn of Synthetic Eracited by 13
  8. 2024Explore In-Context Segmentation via Latent Diffusion Modelscited by 12
  9. 2024MaskDiffusion: Exploiting Pre-trained Diffusion Models for Semantic Segmentationcited by 11
  10. 2024ControlUDA: Controllable Diffusion-assisted Unsupervised Domain Adaptation for Cross-Weather Semantic Segmentationcited by 6
  11. 2024AgMTR: Agent Mining Transformer for Few-shot Segmentation in Remote Sensingcited by 6
  12. 2024FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image Translationcited by 5
10 more
  1. 2024Data Augmentation via Latent Diffusion for Saliency Predictioncited by 5
  2. 2024DODA: Adapting Object Detectors to Dynamic Agricultural Environments in Real-Time with Diffusioncited by 4
  3. 2024Auto Cherry-Picker: Learning from High-quality Generative Data Driven by Languagecited by 4
  4. 2025Conditional Latent Diffusion Models for Zero-Shot Instance Segmentationcited by 4
  5. 2024Group-On: Boosting One-Shot Segmentation with Supportive Querycited by 3
  6. 2024Denoising Diffusion Models for Anomaly Localization in Medical Imagescited by 3
  7. 2025O3Afford: One-Shot 3D Object-to-Object Affordance Grounding for Generalizable Robotic Manipulationcited by 3
  8. 2025Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Reviewcited by 1
  9. 2026Make It Up: Fake Images, Real Gains in Generalized Few-shot Semantic Segmentationcited by 1
  10. 2025Harnessing the Power of Training-Free Techniques in Text-to-2D Generation for Text-to-3D Generation via Score Distillation Samplingcited by 0

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  1. 2024Diffusion Features to Bridge Domain Gap for Semantic Segmentation
  2. 2023Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter
  3. 2024High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
  4. 2024No Re-Train, More Gain: Upgrading Backbones with Diffusion model for Pixel-Wise and Weakly-Supervised Few-Shot Segmentation
  5. 2024Zero-Shot Video Semantic Segmentation based on Pre-Trained Diffusion Models
  6. 2023Denoising Diffusion Semantic Segmentation with Mask Prior Modeling
  7. 2023DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models
  8. 2024EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models