mlsanityData to 13 Oct 2026

Non-Rigid Puzzles

arXiv 2011.13076 ↗First posted 26 Nov 2020cs.CV cs.GRcited by 18

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Abstract (arXiv)

Shape correspondence is a fundamental problem in computer graphics and vision, with applications in various problems including animation, texture mapping, robotic vision, medical imaging, archaeology and many more. In settings where the shapes are allowed to undergo non-rigid deformations and only partial views are available, the problem becomes very challenging. To this end, we present a non-rigid multi-part shape matching algorithm. We assume to be given a reference shape and its multiple parts undergoing a non-rigid deformation. Each of these query parts can be additionally contaminated by clutter, may overlap with other parts, and there might be missing parts or redundant ones. Our method simultaneously solves for the segmentation of the reference model, and for a dense correspondence to (subsets of) the parts. Experimental results on synthetic as well as real scans demonstrate the effectiveness of our method in dealing with this challenging matching scenario.

Key facts. Cited by 18 papers in the map (data through 13 Oct 2026). First posted on arXiv 26 Nov 2020.

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

18 papers.

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  1. 2021Lepard: Learning partial point cloud matching in rigid and deformable scenescited by 85
  2. 2021NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Gocited by 81
  3. 2022A Survey of Non-Rigid 3D Registrationcited by 59
  4. 2021DPFM: Deep Partial Functional Mapscited by 58
  5. 2022Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priorscited by 42
  6. 2023Understanding and Improving Features Learned in Deep Functional Mapscited by 20
  7. 2022A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matchingcited by 19
  8. 2024Partial-to-Partial Shape Matching with Geometric Consistencycited by 16
  9. 2023Geometrically Consistent Partial Shape Matchingcited by 13
  10. 2024SRIF: Semantic Shape Registration Empowered by Diffusion-based Image Morphing and Flow Estimationcited by 12
  11. 2024Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Surface Matching Algorithmscited by 11
  12. 2022G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priorscited by 8
6 more
  1. 2024Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstructioncited by 7
  2. 2021Learning Spectral Unions of Partial Deformable 3D Shapescited by 4
  3. 2025FRIDU: Functional Map Refinement with Guided Image Diffusioncited by 4
  4. 2021Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fieldscited by 1
  5. 2022Partial Shape Similarity via Alignment of Multi-Metric Hamiltonian Spectracited by 1
  6. 2025The Joint Gromov Wasserstein Objective for Multiple Object Matchingcited by 0