The fisheye camera, with its large viewing angle, can acquire more spatial information in
one shot and is widely used in many fields. However, a fisheye image contains large …

Camera calibration involves estimating camera parameters to infer geometric features from
captured sequences, which is crucial for computer vision and robotics. However …

Camera lenses often suffer from optical aberrations, causing radial distortion in the captured
images. In those images, there exists a clear and general physical distortion model …

Object detection in top-view fisheye cameras is more difficult than standard cameras. This
article summarizes the issues regarding object detection accuracy in top-view fisheye …

Fisheye image rectification is hindered by synthetic models producing poor results for real-
world correction. To address this, we propose a Dual Diffusion Architecture (DDA) for fisheye …

The accuracy of the visual tasks for top-view fisheye cameras is limited by the Euclidean
geometry for pose-distorted objects in images. In this paper, we demonstrate the analogy …

Wide-angle video frames typically contain more information, but they also exhibit distortion
that degrades the visual quality, especially at the edges. To eliminate this distortion from …

It has long been recognized that the standard convolution is not rotation equivariant and
thus not appropriate for downside fisheye images which are rotationally symmetric. This …

Numerous significant progress on fisheye image rectification has been achieved through
CNN. Nevertheless, constrained by a fixed receptive field, the global distribution and the …

With the development of deep learning in recent years, the performance of object detection
under conventional cameras has been significantly improved. Nevertheless, due to the …