A Benchmark and Evaluation of Non-Rigid Structure from Motion

Sebastian Hoppe Nesgaard Jensen, Mads Emil Brix Doest, Henrik Aanæs, Alessio Del Bue

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Non-rigid structure from motion (nrsfm), is a long standing and central problem in computer vision and its solution is necessary for obtaining 3D information from multiple images when the scene is dynamic. A main issue regarding the further development of this important computer vision topic, is the lack of high quality data sets. We here address this issue by presenting a data set created for this purpose, which is made publicly available, and considerably larger than the previous state of the art. To validate the applicability of this data set, and provide an investigation into the state of the art of nrsfm, including potential directions forward, we here present a benchmark and a scrupulous evaluation using this data set. This benchmark evaluates 18 different methods with available code that reasonably spans the state of the art in sparse nrsfm. This new public data set and evaluation protocol will provide benchmark tools for further development in this challenging field.
Original languageEnglish
JournalInternational Journal of Computer Vision
Number of pages18
Publication statusPublished - 2020

Bibliographical note

Special Issue on Performance Evaluation in Computer Vision.


  • Non-rigid structure from motion
  • Dataset
  • Evaluation
  • Deformation modelling


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