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CVPR 2025

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

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

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摘要

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.