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

Giorgos Sfikas, Konstantina Nikolaidou, Foteini Papadopoulou, George Retsinas, Anastasios L. Kesidis
11/4/2025
cs.CV

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Abstract

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.

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Cite this paper

@article{sfikas2025euler,
  title  = {Are Euler angles a useful rotation parameterisation for pose estimation with Normalizing Flows?},
  author = {Giorgos Sfikas and Konstantina Nikolaidou and Foteini Papadopoulou and George Retsinas and Anastasios L. Kesidis},
  year   = {2025},
  eprint = {2511.02277},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2511.02277v1}
}

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