Style Agnostic 3D Reconstruction via Adversarial Style Transfer

@article{Petersen2022StyleA3,
  title={Style Agnostic 3D Reconstruction via Adversarial Style Transfer},
  author={Felix Petersen and Bastian Goldluecke and Oliver Deussen and Hilde Kuehne},
  journal={2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
  year={2022},
  pages={2273-2282}
}
Reconstructing the 3D geometry of an object from an image is a major challenge in computer vision. Recently introduced differentiable renderers can be leveraged to learn the 3D geometry of objects from 2D images, but those approaches require additional supervision to enable the renderer to produce an output that can be compared to the input image. This can be scene information or constraints such as object silhouettes, uniform backgrounds, material, texture, and lighting. In this paper, we… 
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