目录

目录

SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images


<SDF-SRN> SDF-SRN: Learning signed distance 3D object reconstruction from static images

编者按

  • 训练时需要single view silhouette

Motivation

  • 单视角3D物体重建,过去的方法往往都有3D形状真值
  • 最近的方法可以没有3D监督信号,但是还是需要训练时多视角的对同个instance的silhouettes标注;因此大多只能应对合成数据集
  • 本篇提出SDF-SRN,只需要单视角图片(只在训练时+silhouette)输入
    https://longtimenohack.com/posts/paper_reading/2020nips_lin_sdf/image-20201221153940813.png

overview

  • single-view一般需要encoder
    https://longtimenohack.com/posts/paper_reading/2020nips_lin_sdf/image-20201215173359177.png

Results

  • 学出的形状奇奇怪怪;不过总归是纯图片输入,而且只有训练时需要silhouette
    https://longtimenohack.com/posts/paper_reading/2020nips_lin_sdf/image-20201221153429857.png
  • 颜色重建的质量也一般
    https://longtimenohack.com/posts/paper_reading/2020nips_lin_sdf/image-20201221155058978.png