mlsanityData to 14 Oct 2026

Quantum Multi-Model Fitting

arXiv 2303.15444 ↗First posted 27 Mar 2023cs.CVcited by 12

Not on the map. Why?

Abstract (arXiv)

Geometric model fitting is a challenging but fundamental computer vision problem. Recently, quantum optimization has been shown to enhance robust fitting for the case of a single model, while leaving the question of multi-model fitting open. In response to this challenge, this paper shows that the latter case can significantly benefit from quantum hardware and proposes the first quantum approach to multi-model fitting (MMF). We formulate MMF as a problem that can be efficiently sampled by modern adiabatic quantum computers without the relaxation of the objective function. We also propose an iterative and decomposed version of our method, which supports real-world-sized problems. The experimental evaluation demonstrates promising results on a variety of datasets. The source code is available at: https://github.com/FarinaMatteo/qmmf.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 20 of its 59 references that are in the map. First posted on arXiv 27 Mar 2023.

Builds on

20 of 59 references.

References · 20

  1. 2019Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithmcited by 43
  2. 2021Quantum Permutation Synchronizationcited by 32
  3. 2021Q-Match: Iterative Shape Matching via Quantum Annealingcited by 27
  4. 2014A practical heuristic for finding graph minorscited by 26
  5. 2019A Quantum Computational Approach to Correspondence Problems on Point Setscited by 23
  6. 2022Adiabatic Quantum Computing for Multi Object Trackingcited by 22
  7. 2021Adiabatic Quantum Graph Matching with Permutation Matrix Constraintscited by 20
  8. 2017Multi-Class Model Fitting by Energy Minimization and Mode-Seekingcited by 19
  9. 2020Quantum-soft QUBO Suppression for Accurate Object Detectioncited by 19
  10. 2022A Hybrid Quantum-Classical Algorithm for Robust Fittingcited by 16
  11. 2022Quantum Motion Segmentationcited by 16
  12. 2022Semiconductor Defect Detection by Hybrid Classical-Quantum Deep Learningcited by 16
8 more
  1. 2020Quantum Robust Fittingcited by 15
  2. 2018Searching for Representative Modes on Hypergraphs for Robust Geometric Model Fittingcited by 8
  3. 2022Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimizationcited by 8
  4. 2020Hypergraph Optimization for Multi-structural Geometric Model Fittingcited by 5
  5. 2016Mode-Seeking on Hypergraphs for Robust Geometric Model Fittingcited by 4
  6. 2016Hypergraph Modelling for Geometric Model Fittingcited by 4
  7. 2016Nonnegative Matrix Underapproximation for Robust Multiple Model Fittingcited by 4
  8. 2014A Bi-clustering Framework for Consensus Problemscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 1; 2025: 5; 2026: 2.

12 papers.

  1. 2025Quantum Visual Fields with Neural Amplitude Encodingcited by 6
  2. 20233D-QAE: Fully Quantum Auto-Encoding of 3D Point Cloudscited by 5
  3. 2024Robust Fitting on a Gate Quantum Computercited by 5
  4. 2025Quantum-enhanced Computer Vision: Going Beyond Classical Algorithmscited by 5
  5. 2023Probabilistic Sampling of Balanced K-Means using Adiabatic Quantum Computingcited by 3
  6. 2023Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradientscited by 3
  7. 2023Quantum Annealing for Computer Vision Minimization Problemscited by 2
  8. 2025Outlier-Robust Multi-Model Fitting on Quantum Annealerscited by 1
  9. 2026Quantum Multiple Rotation Averagingcited by 1
  10. 2025Accelerating Outlier-robust Rotation Estimation by Stereographic Projectioncited by 0
  11. 2025HQC-NBV: A Hybrid Quantum-Classical View Planning Approachcited by 0
  12. 2026Robust Multi-Model Fitting through Learning Neighbor Regionscited by 0