Homography estimation is an important task in computer vision applications, such as image
stitching, video stabilization, and camera calibration. Traditional homography estimation …

Feature detection and correct matching are the basis of the image stitching process.
Whether the matching is correct and the number of matches directly affect the quality of the …

Homography estimation is a fundamental task in computer vision that involves obtaining the
transformation between multiview images for image alignment. Although convolutional …

Due to the parallax of input image sequence, it is difficult to achieve accurate alignment,
which results in artifacts in image stitching. Besides, since most spatial variation warps …

Homography estimation aligns image pairs in cross-views, which is a crucial and
fundamental computer vision problem. Existing methods only consider correspondences of …

Homography estimation is a critical component in many computer-vision tasks. However,
most deep homography methods focus on extracting local features and ignore global …

Homography estimation is essential for aligning images captured from different viewpoints
by accurately modeling the geometric relationship between them. In homography estimation …

The digital construction of cultural heritage promotes communication and sharing of digital
cultural resources across time and space. Digital storage serves as the foundation for the …

Image stitching with large parallax poses a significant challenge in the field of computer
vision. Existing seam-based approaches attempt to address parallax artifacts by stitching …

Image alignment with parallax is a challenging computer vision problem. While existing
methods employing local-varying smooth warps have enhanced alignment accuracy for …