Browsing Volume 39 (2020) by Subject "3D shape matching"

Now showing items 1-3 of 3

    • FARM: Functional Automatic Registration Method for 3D Human Bodies 

      Marin, R.; Melzi, S.; Rodolà, E.; Castellani, U. (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020)
      We introduce a new method for non‐rigid registration of 3D human shapes. Our proposed pipeline builds upon a given parametric model of the human, and makes use of the functional map representation for encoding and inferring ...

    • SiamesePointNet: A Siamese Point Network Architecture for Learning 3D Shape Descriptor 

      Zhou, J.; Wang, M. J.; Mao, W. D.; Gong, M. L.; Liu, X. P. (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020)
      We present a novel deep learning approach to extract point‐wise descriptors directly on 3D shapes by introducing Siamese Point Networks, which contain a global shape constraint module and a feature transformation operator. ...

    • ZerNet: Convolutional Neural Networks on Arbitrary Surfaces Via Zernike Local Tangent Space Estimation 

      Sun, Zhiyu; Rooke, Ethan; Charton, Jerome; He, Yusen; Lu, Jia; Baek, Stephen (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020)
      In this paper, we propose a novel formulation extending convolutional neural networks (CNN) to arbitrary two‐dimensional manifolds using orthogonal basis functions called Zernike polynomials. In many areas, geometric ...