mlsanityData to 14 Oct 2026

A review of mean-shift algorithms for clustering

arXiv 1503.00687 ↗First posted 2 Mar 2015cs.LG cs.CV stat.MLcited by 19

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Abstract (arXiv)

A natural way to characterize the cluster structure of a dataset is by finding regions containing a high density of data. This can be done in a nonparametric way with a kernel density estimate, whose modes and hence clusters can be found using mean-shift algorithms. We describe the theory and practice behind clustering based on kernel density estimates and mean-shift algorithms. We discuss the blurring and non-blurring versions of mean-shift; theoretical results about mean-shift algorithms and Gaussian mixtures; relations with scale-space theory, spectral clustering and other algorithms; extensions to tracking, to manifold and graph data, and to manifold denoising; K-modes and Laplacian K-modes algorithms; acceleration strategies for large datasets; and applications to image segmentation, manifold denoising and multivalued regression.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Mar 2015.

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Citing papers per year: 2021: 4; 2022: 0; 2023: 4; 2024: 4; 2025: 5; 2026: 2.

19 papers.

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  1. 2024On the Trajectory Regularity of ODE-based Diffusion Samplingcited by 55
  2. 2023A Geometric Perspective on Diffusion Modelscited by 18
  3. 2025Weighted quantization using MMD: From mean field to mean shift via gradient flowscited by 12
  4. 2021Transductive Few-Shot Learning: Clustering is All You Need?cited by 4
  5. 2024On the number of modes of Gaussian kernel density estimatorscited by 4
  6. 2025Geometric Regularity in Deterministic Sampling Dynamics of Diffusion-based Generative Modelscited by 4
  7. 2023Enhancing Interpretable Object Abstraction via Clustering-based Slot Initializationcited by 3
  8. 2021Skeleton Clustering: Dimension-Free Density-based Clusteringcited by 2
  9. 2023UniForCE: The Unimodality Forest Method for Clustering and Estimation of the Number of Clusterscited by 2
  10. 2021The EM Perspective of Directional Mean Shift Algorithmcited by 1
  11. 2021Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approachcited by 1
  12. 2024Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learningcited by 1
7 more
  1. 2023StructuredMesh: 3D Structured Optimization of Faccade Components on Photogrammetric Mesh Models using Binary Integer Programmingcited by 0
  2. 2024Emergenet: A Digital Twin of Sequence Evolution for Scalable Emergence Risk Assessment of Animal Influenza A Strainscited by 0
  3. 2025What Does Normal Even Mean? Evaluating Benign Traffic in Intrusion Detection Datasetscited by 0
  4. 2025Hyperbolic Gaussian Blurring Mean Shift: A Statistical Mode-Seeking Framework for Clustering in Curved Spacescited by 0
  5. 2025MoE-TransMov: A Transformer-based Model for Next POI Prediction in Familiar & Unfamiliar Movementscited by 0
  6. 2026Federated Hierarchical Clustering with Automatic Selection of Optimal Cluster Numberscited by 0
  7. 2026Gradient-Guided Density Peak Clusteringcited by 0