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

Kevin Zhang, Jia-Bin Huang, Jose Echevarria, Stephen DiVerdi, Aaron Hertzmann; Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), 2025, pp. 10923-10932

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.

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[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} }