CVPR 2025poster0 citations

MaDCoW: Marginal Distortion Correction for Wide-Angle Photography with Arbitrary Objects

Kevin Zhang, Jia-Bin Huang, Jose Echevarria, Stephen DiVerdi, Aaron Hertzmann

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.

BibTeX
@InProceedings{Zhang_2025_CVPR,
    author    = {Zhang, Kevin and Huang, Jia-Bin and Echevarria, Jose and DiVerdi, Stephen and Hertzmann, Aaron},
    title     = {MaDCoW: Marginal Distortion Correction for Wide-Angle Photography with Arbitrary Objects},
    booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
    month     = {June},
    year      = {2025},
    pages     = {10923-10932}
}
MaDCoW: Marginal Distortion Correction for Wide-Angle Photography with Arbitrary Objects · CVPR 2025