Moreover, different camera settings are required for different scenes in terms of the scene窶冱 maximum depth,i.e. for KITTI, we consider maximum depth of 80 meters, and 10 meters for NYU.
contains over 93 thousand depth maps with corresponding raw LiDaR scans and RGB images, aligned with the "raw data" of the KITTI dataset. Given the large amount of training data, this dataset shall allow a training of complex deep learning models for the tasks of depth completion and single image depth prediction.
Oct 01, 2019 · Quantitative comparisons of monocular depth estimation on the KITTI dataset with existing approaches. K and CS represent the KITTI dataset and Cityscapes respectively. Our proposed method performs excellently among the monocular methods and is quite close to the stereo methods in terms of a2 and a3.
David Eigen, ChristianPuhrsch,andRobFergus.Depth map prediction from a single image using a multi-scale deep network. In NIPS*2014, pages 2366–2374. and here a brief summary about Kitti Split and Eigen Split: The KITTI-Raw dataset contains 42,382 stereo image pairs grouped into 61 scenes. Image sizes 1242×375.