Parallelly Sliced Optimal Transport on Spheres and on the Rotation Group
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Abstract (arXiv)
Sliced optimal transport, which is basically a Radon transform followed by one-dimensional optimal transport, became popular in various applications due to its efficient computation. In this paper, we deal with sliced optimal transport on the sphere mathbbSd-1 and on the rotation group SO(3). We propose a parallel slicing procedure of the sphere which requires again only optimal transforms on the line. We analyze the properties of the corresponding parallelly sliced optimal transport, which provides in particular a rotationally invariant metric on the spherical probability measures. For SO(3), we introduce a new two-dimensional Radon transform and develop its singular value decomposition. Based on this, we propose a sliced optimal transport on SO(3). As Wasserstein distances were extensively used in barycenter computations, we derive algorithms to compute the barycenters with respect to our new sliced Wasserstein distances and provide synthetic numerical examples on the 2-sphere that demonstrate their behavior for both the free and fixed support setting of discrete spherical measures. In terms of computational speed, they outperform the existing methods for semicircular slicing as well as the regularized Wasserstein barycenters.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jan 2024.
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Citing papers per year: 2024: 3; 2025: 5; 2026: 2.
10 papers.
- 2025Lightspeed Geometric Dataset Distance via Sliced Optimal Transportcited by 10
- 2025Slicing the Gaussian Mixture Wasserstein Distancecited by 7
- 2024Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributionscited by 6
- 2025Slicing Wasserstein Over Wasserstein Via Functional Optimal Transportcited by 5
- 2024Optimal Transport on the Lie Group of Roto-translationscited by 4
- 2024Relative Translation Invariant Wasserstein Distancecited by 3
- 2025Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classificationcited by 3
- 2025Generalizations of the Normalized Radon Cumulative Distribution Transform for Limited Data Recognitioncited by 0
- 2026HOT-POT: Optimal Transport for Sparse Stereo Matchingcited by 0
- 2026Application and Evaluation of the Common Circles Methodcited by 0
- 2026Application and Evaluation of the Common Circles Method19 Feb 2026
- 2026HOT-POT: Optimal Transport for Sparse Stereo Matching18 Jan 2026
- 2025Generalizations of the Normalized Radon Cumulative Distribution Transform for Limited Data Recognition8 Dec 2025
- 2025Slicing Wasserstein Over Wasserstein Via Functional Optimal Transport26 Sep 2025
- 2025Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification10 Jun 2025
- 2025Slicing the Gaussian Mixture Wasserstein Distance11 Apr 2025
- 2025Lightspeed Geometric Dataset Distance via Sliced Optimal Transport31 Jan 2025
- 2024Relative Translation Invariant Wasserstein Distance4 Sep 2024
- 2024Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions23 Apr 2024
- 2024Optimal Transport on the Lie Group of Roto-translations23 Feb 2024