mlsanityData to 7 Oct 2026

Are Euler angles a useful rotation parameterisation for pose estimation with Normalizing Flows?

arXiv 2511.02277 ↗First posted 4 Nov 2025cs.CVcited by 2

Not on the map. Why?

Abstract (arXiv)

Object pose estimation is a task that is of central importance in 3D Computer Vision. Given a target image and a canonical pose, a single point estimate may very often be sufficient; however, a probabilistic pose output is related to a number of benefits when pose is not unambiguous due to sensor and projection constraints or inherent object symmetries. With this paper, we explore the usefulness of using the well-known Euler angles parameterisation as a basis for a Normalizing Flows model for pose estimation. Isomorphic to spatial rotation, 3D pose has been parameterized in a number of ways, either in or out of the context of parameter estimation. We explore the idea that Euler angles, despite their shortcomings, may lead to useful models in a number of aspects, compared to a model built on a more complex parameterisation.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 33 references that are in the map. First posted on arXiv 4 Nov 2025.

Builds on

14 of 33 references.

References · 14

  1. 2018Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objectscited by 237
  2. 2021Probabilistic Modeling for Human Mesh Recoverycited by 152
  3. 2020Riemannian Continuous Normalizing Flowscited by 143
  4. 2020Normalizing Flows on Tori and Spherescited by 117
  5. 2024Normalizing Flows are Capable Generative Modelscited by 89
  6. 2020Neural Manifold Ordinary Differential Equationscited by 81
  7. 2021Moser Flow: Divergence-based Generative Modeling on Manifoldscited by 67
  8. 2018Deep Directional Statistics: Pose Estimation with Uncertainty Quantificationcited by 45
  9. 2020Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimationcited by 43
  10. 2019Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spherescited by 37
  11. 2020Probabilistic orientation estimation with matrix Fisher distributionscited by 36
  12. 2020Neural Ordinary Differential Equations on Manifoldscited by 31
2 more
  1. 2023Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modelingcited by 14
  2. 2023Piecewise Normalizing Flowscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Revisiting Euler-Angle Regression with Kolmogorov-Arnold Networkscited by 0
  2. 2026CQF-HMR: Continuous Quaternion Flows for Probabilistic 3D Human Mesh Recovery from a Single Imagecited by 0