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arXiv Computer Vision By Yuhao Shan, Qianyi Yuan, Jingguo Liu, Shigang Li, Jianfeng Li, Tong Chen

Learning Projection-Aware 360-Degree Image Rectification via Dual-Projection Fusion

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The paper introduces a dual‑projection framework for rectifying 360° panoramic images, combining a convolutional neural network that processes equirectangular projections with a vision transformer that handles cubemap projections. Cross‑projection feature transformation and multi‑level fusion allow the two representations to interact, supporting collaborative inclination estimation and upright panorama generation. Experiments on SUN360 and M3D demonstrate significant accuracy gains, achieving 65.9% and 85.2% within a 1° error threshold and low Fréchet Inception Distance scores.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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