3 papers
cs.CV2020
BP-MVSNet: Belief-Propagation-Layers for Multi-View-Stereo
Christian Sormann, Patrick Knöbelreiter, Andreas Kuhn +3
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 re…
cs.CV2019
Joint Graph-based Depth Refinement and Normal Estimation
Mattia Rossi, Mireille El Gheche, Andreas Kuhn +1
Depth estimation is an essential component in understanding the 3D geometry of a scene, with numerous applications in urban and indoor settings. These scenes are characterized by a…
cs.CV2019
DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction
Andreas Kuhn, Christian Sormann, Mattia Rossi +2
Deep Neural Networks (DNNs) have the potential to improve the quality of image-based 3D reconstructions. However, the use of DNNs in the context of 3D reconstruction from large and…