mlsanityData to 7 Oct 2026

ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts

arXiv 2301.12276 ↗First posted 28 Jan 2023cs.CVcited by 33

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Abstract (arXiv)

We introduce ProtoSeg, a novel model for interpretable semantic image segmentation, which constructs its predictions using similar patches from the training set. To achieve accuracy comparable to baseline methods, we adapt the mechanism of prototypical parts and introduce a diversity loss function that increases the variety of prototypes within each class. We show that ProtoSeg discovers semantic concepts, in contrast to standard segmentation models. Experiments conducted on Pascal VOC and Cityscapes datasets confirm the precision and transparency of the presented method.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). Builds on 64 of its 81 references that are in the map. First posted on arXiv 28 Jan 2023.

Builds on

64 of 81 references.

References · 64

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  4. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  5. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  6. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,690
  7. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,040
  8. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  9. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  10. 2016DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFscited by 3,239
  11. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  12. 2016Pyramid Scene Parsing Networkcited by 2,472
38 more
  1. 2013Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Mapscited by 2,348
  2. 2017Non-local Neural Networkscited by 2,290
  3. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  4. 2020Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformerscited by 1,368
  5. 2017Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)cited by 1,309
  6. 2018Sanity Checks for Saliency Mapscited by 1,149
  7. 2020Concept Bottleneck Modelscited by 1,022
  8. 2021Segmenter: Transformer for Semantic Segmentationcited by 855
  9. 2018This Looks Like That: Deep Learning for Interpretable Image Recognitioncited by 731
  10. 2014Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognitioncited by 719
  11. 2020Image Segmentation Using Deep Learning: A Surveycited by 659
  12. 2019Explaining Machine Learning Classifiers through Diverse Counterfactual Explanationscited by 612
  13. 2017Interpretable Explanations of Black Boxes by Meaningful Perturbationcited by 611
  14. 2014Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFscited by 552
  15. 2018Towards Robust Interpretability with Self-Explaining Neural Networkscited by 505
  16. 2021Semi-Supervised Semantic Segmentation with Cross Pseudo Supervisioncited by 462
  17. 2021Interpretable Machine Learning: Fundamental Principles and 10 Grand Challengescited by 364
  18. 2019Counterfactual Visual Explanationscited by 312
  19. 2020Counterfactual VQA: A Cause-Effect Look at Language Biascited by 266
  20. 2019Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNetcited by 260
  21. 2019Understanding Deep Networks via Extremal Perturbations and Smooth Maskscited by 257
  22. 2019On Completeness-aware Concept-Based Explanations in Deep Neural Networkscited by 239
  23. 2017Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictionscited by 234
  24. 2020Concept Whitening for Interpretable Image Recognitioncited by 225
  25. 2020Neural Prototype Trees for Interpretable Fine-grained Image Recognitioncited by 213
  26. 2015ParseNet: Looking Wider to See Bettercited by 176
  27. 2019Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Groundedcited by 127
  28. 2014Learning Rich Features from RGB-D Images for Object Detection and Segmentationcited by 124
  29. 2021Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypescited by 120
  30. 2021Interpretable Image Classification with Differentiable Prototypes Assignmentcited by 97
  31. 2021ProtGNN: Towards Self-Explaining Graph Neural Networkscited by 96
  32. 2021Multi-Scale High-Resolution Vision Transformer for Semantic Segmentationcited by 92
  33. 2020ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discoverycited by 89
  34. 2017Learning Affinity via Spatial Propagation Networkscited by 79
  35. 2019Interpretable and Steerable Sequence Learning via Prototypescited by 72
  36. 2021XProtoNet: Diagnosis in Chest Radiography with Global and Local Explanationscited by 72
  37. 2021IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammographycited by 72
  38. 2015Efficient piecewise training of deep structured models for semantic segmentationcited by 71

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 12; 2025: 11; 2026: 6.

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  1. 2023Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanationscited by 27
  2. 2023ICICLE: Interpretable Class Incremental Continual Learningcited by 24
  3. 2023Pixel-Grounded Prototypical Part Networkscited by 18
  4. 2025A Comprehensive Survey on Self-Interpretable Neural Networkscited by 18
  5. 2024LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Visioncited by 15
  6. 2024Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Surveycited by 11
  7. 2024This Looks Better than That: Better Interpretable Models with ProtoPNeXtcited by 10
  8. 2024A survey on Concept-based Approaches For Model Improvementcited by 8
  9. 2024XEdgeAI: A Human-centered Industrial Inspection Framework with Data-centric Explainable Edge AI Approachcited by 7
  10. 2024Aggregated Attributions for Explanatory Analysis of 3D Segmentation Modelscited by 5
  11. 2024Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learningcited by 4
  12. 2024Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentationcited by 4
21 more
  1. 2024An Overview of Prototype Formulations for Interpretable Deep Learningcited by 4
  2. 2024Cross- and Intra-image Prototypical Learning for Multi-label Disease Diagnosis and Interpretationcited by 4
  3. 2025Interpretable Affordance Detection on 3D Point Clouds with Probabilistic Prototypescited by 3
  4. 2025SIDE: Sparse Information Disentanglement for Explainable Artificial Intelligencecited by 3
  5. 2025LPD: Learnable Prototypes with Diversity Regularization for Weakly Supervised Histopathology Segmentationcited by 2
  6. 2024ProtoP-OD: Explainable Object Detection with Prototypical Partscited by 1
  7. 2024MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor Classificationcited by 1
  8. 2025COMIX: Compositional Explanations using Prototypescited by 1
  9. 2025Comprehensive Evaluation of Prototype Neural Networkscited by 1
  10. 2026T-DuMpRa: Teacher-guided Dual-path Multi-prototype Retrieval Augmented framework for fine-grained medical image classificationcited by 1
  11. 2023Leveraging Habitat Information for Fine-grained Bird Identificationcited by 0
  12. 2025CanadaFireSat: Toward high-resolution wildfire forecasting with multiple modalitiescited by 0
  13. 2025Deeply Dual Supervised learning for melanoma recognitioncited by 0
  14. 2025Edge Detection for Organ Boundaries via Top Down Refinement and SubPixel Upsamplingcited by 0
  15. 2025DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentationcited by 0
  16. 2025VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagationcited by 0
  17. 2026ProtoQuant: Quantization of Prototypical Parts For General and Fine-Grained Image Classificationcited by 0
  18. 2026RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosiscited by 0
  19. 2026BP-TTA: Balanced and Prototype-Guided Test-Time Adaptation in Dynamic Scenarioscited by 0
  20. 2026Generative Semantic Segmentation via an Observable Semantic-Image Interface and Hierarchical Generator Evidence Alignmentcited by 0
  21. 2026PiPS: Post-Hoc Prototypical Explanations for Interpretable Semantic Segmentationcited by 0