mlsanityData to 7 Oct 2026

Deep Feature Factorization For Concept Discovery

arXiv 1806.10206 ↗First posted 26 Jun 2018cs.LG cs.CV stat.MLcited by 64

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Abstract (arXiv)

We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images. We use DFF to gain insight into a deep convolutional neural network's learned features, where we detect hierarchical cluster structures in feature space. This is visualized as heat maps, which highlight semantically matching regions across a set of images, revealing what the network `perceives' as similar. DFF can also be used to perform co-segmentation and co-localization, and we report state-of-the-art results on these tasks.

Key facts. Cited by 64 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jun 2018.

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Citing papers per year: 2021: 11; 2022: 14; 2023: 12; 2024: 16; 2025: 8; 2026: 3.

64 papers.

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  1. 2021GAN Inversion: A Surveycited by 366
  2. 2021Deep ViT Features as Dense Visual Descriptorscited by 327
  3. 2022Unsupervised Semantic Segmentation by Distilling Feature Correspondencescited by 241
  4. 2022Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localizationcited by 150
  5. 2022ReCo: Retrieve and Co-segment for Zero-shot Transfercited by 115
  6. 2021PartImageNet: A Large, High-Quality Dataset of Partscited by 107
  7. 2022LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discoverycited by 65
  8. 2021Unsupervised Part Discovery from Contrastive Reconstructioncited by 57
  9. 2021Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentationcited by 31
  10. 2022Hi-LASSIE: High-Fidelity Articulated Shape and Skeleton Discovery from Sparse Image Ensemblecited by 30
  11. 2021Unsupervised Part Segmentation through Disentangling Appearance and Shapecited by 29
  12. 2023Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic Segmentationcited by 26
38 more
  1. 2021Linear Semantics in Generative Adversarial Networkscited by 25
  2. 2022DeepCut: Unsupervised Segmentation using Graph Neural Networks Clusteringcited by 25
  3. 2023PDiscoNet: Semantically consistent part discovery for fine-grained recognitioncited by 21
  4. 2022PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANscited by 20
  5. 2021GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generationcited by 19
  6. 2022AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypointscited by 17
  7. 2022Neural Networks are Decision Treescited by 16
  8. 2023Unsupervised Keypoints from Pretrained Diffusion Modelscited by 15
  9. 2021Unsupervised Co-part Segmentation through Assemblycited by 12
  10. 2024Interpreting and Analysing CLIP's Zero-Shot Image Classification via Mutual Knowledgecited by 12
  11. 2022Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face Generationcited by 8
  12. 2024Benchmarking XAI Explanations with Human-Aligned Evaluationscited by 8
  13. 2022HP-Capsule: Unsupervised Face Part Discovery by Hierarchical Parsing Capsule Networkcited by 7
  14. 2023Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentationcited by 7
  15. 2023Optical Flow boosts Unsupervised Localization and Segmentationcited by 7
  16. 2024Post-hoc Part-prototype Networkscited by 7
  17. 2023Unsupervised Discovery of 3D Hierarchical Structure with Generative Diffusion Featurescited by 4
  18. 2024Unsupervised Object Discovery: A Comprehensive Survey and Unified Taxonomycited by 4
  19. 2024CALICO: Part-Focused Semantic Co-Segmentation with Large Vision-Language Modelscited by 4
  20. 2023Graphics Capsule: Learning Hierarchical 3D Face Representations from 2D Imagescited by 3
  21. 2024Masked Multi-Query Slot Attention for Unsupervised Object Discoverycited by 3
  22. 2024Segmentation by Factorization: Unsupervised Semantic Segmentation for Pathology by Factorizing Foundation Model Featurescited by 3
  23. 2021Stochastic Block-ADMM for Training Deep Networkscited by 2
  24. 2021Self-Supervised Object Detection via Generative Image Synthesiscited by 2
  25. 2022LEAD: Self-Supervised Landmark Estimation by Aligning Distributions of Feature Similaritycited by 2
  26. 2022Automatic Infectious Disease Classification Analysis with Concept Discoverycited by 2
  27. 2023Interpreting Vision and Language Generative Models with Semantic Visual Priorscited by 2
  28. 2024FFAM: Feature Factorization Activation Map for Explanation of 3D Detectorscited by 2
  29. 2024Composing Parts for Expressive Object Generationcited by 2
  30. 2024Unsupervised Part Discovery via Dual Representation Alignmentcited by 2
  31. 2023Bridging Neural and Symbolic Representations with Transitional Dictionary Learningcited by 1
  32. 2023FM-G-CAM: A Holistic Approach for Explainable AI in Computer Visioncited by 1
  33. 2024Geometric Constraints in Deep Learning Frameworks: A Surveycited by 1
  34. 2024Towards Robust Ferrous Scrap Material Classification with Deep Learning and Conformal Predictioncited by 1
  35. 2024TACO: Training-free Sound Prompted Segmentation via Semantically Constrained Audio-visual CO-factorizationcited by 1
  36. 2025Bottom-Up Scattering Information Perception Network for SAR target recognitioncited by 1
  37. 2025Occlusion-Aware Self-Supervised Monocular Depth Estimation for Weak-Texture Endoscopic Imagescited by 1
  38. 2025Explainable Artificial Intelligence in Biomedical Image Analysis: A Comprehensive Surveycited by 1

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