… belief propagation algorithm on edge regions. To deal with the time consumption issue of the
standard belief propagation … This constraint does not degrade the matching results and can …

… event-based stereo matching algorithm for reliable 3D depth estimation using a method based
… By semi-dense we mean the output is not sparse event points but more dense structures …

In this work, we propose BP-MVSNet, a convolutional neural network (CNN)-based Multi-View-Stereo
(MVS) method that uses a differentiable Conditional Random Field (CRF) layer for …

… for the stereo matching, we propose a semi-supervised learning scheme in which the pixels
classified as confident through the … Yang, “Global stereo matching leveraged by sparse …

… fully support back-propagation through sparse matrix products, we will be able to immediately
back-propagate through belief propagation. Backpropagating through inference has been …

… For stereo matching, PatchMatch belief propagation (PMBP) gives an efficient way of inferencing
… in the high-resolution image using the sparsely arranged disparity values as in Fig. 2a. …

… Abstract: Stereo matching between two images is done by computing disparity of all points
… The accuracy of the object while selecting feature is missing which yields to sparse disparity …

… selection problem and proposed a method called local sparse matching (LSM). By imposing
… belief propagation, but our method directly used belief propagation to compute the matching …

… Belief propagation (BP) algorithm still exists some shortages, … , we present a novel stereo
matching algorithm fusing BP and … Yang, Global stereo matching leveraged by sparse ground …

… Most stereo matching models, such as PSM-Net, GA-Net, and AA-Net, can be easily …
Experiments on multiple benchmark datasets show that our method improves stereo matching …