Abstract: We present a method for inferring dense depth from a camera image and a sparse noisy radar point cloud. We first describe the mechanics behind mmWave radar point cloud formation and the ...
Abstract: In the last decade, we have witnessed a high demand for high-resolution devices and screens. 4K and higher becomes a standard video definition, which requires special calculators such as ...
Abstract: Machine learning is a trending topic in the area of computer vision, which makes the machine able to learn about it without being expressly programmed using various algorithms. When a model ...
Abstract: With the increase in the number of remote sensing satellites and imaging modes, the amount of data for acquiring remote sensing images has greatly increased. Effectively and stably ...
Abstract: Although the fusion of images and LiDAR point clouds is crucial to many applications in computer vision, the relative poses of cameras and LiDAR scanners are often unknown. However, due to ...
Abstract: Cross-modality registration between 2D images and 3D point clouds is an important task in autonomous driving and robotics. Existing methods predict the correspondence between images and ...
Abstract: Super-Resolution (SR) reconstructs high-resolution images from low-resolution ones. CNNs and window-attention methods are two major categories of canonical SR models. However, these measures ...
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