Apr 1, 2021 · We propose an end-to-end stitching network, which takes two images with a narrow field of view (FOV) as inputs, and produces a single image with a wide FOV.
In this paper, we propose an end-to-end stitching network, which takes two images with a narrow field of view (FOV) as inputs, and produces a single image ...
Our method estimates multiple homographies to cover the depth differences in the scene and is therefore robust against parallax distortion. In particular, ...
Oct 22, 2024 · The final result is made by warping input images multiple times using the warping maps and then merging warped images with the weight maps.
An end-to-end stitching network, which takes two images with a narrow field of view (FOV) as inputs, and produces a single image with a wide FOV that is ...
End-to-end image stitching network via multi-homography estimation. DY Song, GM Um, HK Lee, D Cho. IEEE Signal Processing Letters 28, 763-767, 2021. 28, 2021.
A curated list of awesome resources for topics related to computational photography via deep learning, which mainly focuses on image alignment and stitching.
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In this paper, we present a cascaded view-free image stitching network based on the global homography, which can eliminate the ghosting effects as much as ...
In order to estimate the homography, a set of corresponding points between the two images must be found, and a mathematical model must be fit to these points.
Aug 25, 2021 · In this paper, we present a deep neural network that estimates homography accurately enough for image stitching of images with small parallax.