Beyond Planar Symmetry: Modeling Human Perception of Reflection and Rotation Symmetries in the Wild

@article{Funk2017BeyondPS,
  title={Beyond Planar Symmetry: Modeling Human Perception of Reflection and Rotation Symmetries in the Wild},
  author={Christopher Funk and Yanxi Liu},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={793-803}
}
  • Christopher Funk, Yanxi Liu
  • Published 11 April 2017
  • Computer Science
  • 2017 IEEE International Conference on Computer Vision (ICCV)
Humans take advantage of real world symmetries for various tasks, yet capturing their superb symmetry perception mechanism with a computational model remains elusive. Motivated by a new study demonstrating the extremely high inter-person accuracy of human perceived symmetries in the wild, we have constructed the first deeplearning neural network for reflection and rotation symmetry detection (Sym-NET), trained on photos from MS-COCO (Microsoft-Common Object in COntext) dataset with nearly 11K… 

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