Weakly-Supervised Stitching Network for Real-World Panoramic Image Generation

نویسندگان

چکیده

AbstractRecently, there has been growing attention on an end-to-end deep learning-based stitching model. However, the most challenging point in is to obtain pairs of input images with a narrow field view and ground truth wide captured from real-world scenes. To overcome this difficulty, we develop weakly-supervised learning mechanism train model without requiring genuine images. In addition, propose that takes multiple fisheye as inputs creates 360\(^{\circ }\) output image equirectangular projection format. particular, our consists color consistency corrections, warping, blending, trained by perceptual SSIM losses. The effectiveness proposed algorithm verified two datasets.KeywordsImage stitching360\(^{\circ panoramic

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ژورنال

عنوان ژورنال: Lecture Notes in Computer Science

سال: 2022

ISSN: ['1611-3349', '0302-9743']

DOI: https://doi.org/10.1007/978-3-031-19787-1_4