3 accepted papers
We propose an unsupervised real-time dense depth completion from a sparse depth map guided by a single image. Our method generates a smooth depth map while preserving discontinuity between different objects. Our key idea is a Binary Anisotropic Diffusion Tensor (B-ADT) which can completely eliminate
Dense 3D maps from wide-angle cameras is beneficial to robotics applications such as navigation and autonomous driving. In this work, we propose a real-time dense 3D mapping method for fisheye cameras without explicit rectification and undistortion. We extend the conventional variational stereo meth
In this letter, we present a method for estimating a dense depth map from a sparse LIDAR point cloud and an image sequence. Our proposed method relies on a directionally biased propagation of known depth to missing areas based on semantic segmentation. Additionally, we classify different object boun