2020
DOI: 10.48550/arxiv.2011.14611
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SIR: Self-supervised Image Rectification via Seeing the Same Scene from Multiple Different Lenses

Abstract: Deep learning has demonstrated its power in image rectification by leveraging the representation capacity of deep neural networks via supervised training based on a largescale synthetic dataset. However, the model may overfit the synthetic images and generalize not well on realworld fisheye images due to the limited universality of a specific distortion model and the lack of explicitly modeling the distortion and rectification process. In this paper, we propose a novel self-supervised image rectification (SIR)… Show more

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