Ladybird: Quasi-Monte Carlo Sampling for Deep Implicit Field Based 3D Reconstruction with Symmetry

@article{Xu2020LadybirdQC,
  title={Ladybird: Quasi-Monte Carlo Sampling for Deep Implicit Field Based 3D Reconstruction with Symmetry},
  author={Yifan Xu and T. Fan and Yi Yuan and Gurprit Singh},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.13393}
}
  • Yifan Xu, T. Fan, +1 author Gurprit Singh
  • Published 2020
  • Computer Science, Physics
  • ArXiv
  • Deep implicit field regression methods are effective for 3D reconstruction from single-view images. However, the impact of different sampling patterns on the reconstruction quality is not well-understood. In this work, we first study the effect of point set discrepancy on the network training. Based on Farthest Point Sampling algorithm, we propose a sampling scheme that theoretically encourages better generalization performance, and results in fast convergence for SGD-based optimization… CONTINUE READING
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