2025
CVPR
CVPR 2025
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.
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Interdisciplinary Bridge
— Computer Science and Computer Vision and Mathematics & Optimization
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Keyword Pioneer
— wide-angle photography
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization
Authors
Topics
Computer Vision > Processing > Image Restoration
Mathematics & Optimization > Optimization > Continuous Optimization
Computer Science > Systems > Computer Graphics
Computer Vision > Processing > Image Processing
Computer Science > Applications > Computer Graphics
Computer Vision > Processing > Image Registration