ML Anthology

Seeing the World in a Bag of Chips

Jeong Joon Park, Aleksander Holynski, Steven M. Seitz
CVPR 2020
doi:10.1109/CVPR42600.2020.00149 /cvpr/2020/park2020cvpr-seeing/

Abstract

We address the dual problems of novel view synthesis and environment reconstruction from hand-held RGBD sensors. Our contributions include 1) modeling highly specular objects, 2) modeling inter-reflections and Fresnel effects, and 3) enabling surface light field reconstruction with the same input needed to reconstruct shape alone. In cases where scene surface has a strong mirror-like material component, we generate highly detailed environment images, revealing room composition, objects, people, buildings, and trees visible through windows. Our approach yields state of the art view synthesis techniques, operates on low dynamic range imagery, and is robust to geometric and calibration errors.

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Text

Park et al. "Seeing the World in a Bag of Chips." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020. doi:10.1109/CVPR42600.2020.00149

Markdown

[Park et al. "Seeing the World in a Bag of Chips." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.](https://mlanthology.org/cvpr/2020/park2020cvpr-seeing/) doi:10.1109/CVPR42600.2020.00149

BibTeX

@inproceedings{park2020cvpr-seeing,
  title     = {{Seeing the World in a Bag of Chips}},
  author    = {Park, Jeong Joon and Holynski, Aleksander and Seitz, Steven M.},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2020},
  doi       = {10.1109/CVPR42600.2020.00149},
  url       = {https://mlanthology.org/cvpr/2020/park2020cvpr-seeing/}
}