MaDCoW: Marginal Distortion Correction for Wide-Angle Photography with Arbitrary Objects
Abstract
We introduce MaDCoW, a method for correcting marginal distortion of arbitrary objects in wide-angle photography. People often use wide-angle photography to convey natural scenes--smartphones typically default to wide-angle photography--but depicting very wide-field-of-view scenes produces distorted object appearance, particularly marginal distortion in linear projections. With MaDCoW, a user annotates regions-of-interest to correct, along with straight lines. For each region, MaDCoW solves for a local-linear perspective projection and then jointly solves for a projection for the whole photograph that minimizes distortion. We show that our method can produce good results in cases where previous methods yield visible distortions.
Cite
Text
Zhang et al. "MaDCoW: Marginal Distortion Correction for Wide-Angle Photography with Arbitrary Objects." Conference on Computer Vision and Pattern Recognition, 2025. doi:10.1109/CVPR52734.2025.01020Markdown
[Zhang et al. "MaDCoW: Marginal Distortion Correction for Wide-Angle Photography with Arbitrary Objects." Conference on Computer Vision and Pattern Recognition, 2025.](https://mlanthology.org/cvpr/2025/zhang2025cvpr-madcow/) doi:10.1109/CVPR52734.2025.01020BibTeX
@inproceedings{zhang2025cvpr-madcow,
title = {{MaDCoW: Marginal Distortion Correction for Wide-Angle Photography with Arbitrary Objects}},
author = {Zhang, Kevin and Huang, Jia-Bin and Echevarria, Jose and DiVerdi, Stephen and Hertzmann, Aaron},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2025},
pages = {10923-10932},
doi = {10.1109/CVPR52734.2025.01020},
url = {https://mlanthology.org/cvpr/2025/zhang2025cvpr-madcow/}
}