Search Results for author:
Found 4 papers, 0 papers with code
IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions
We present a novel deep-learning-based method for Multi-View Stereo.
Ranked #4 on
3D Reconstruction
on DTU
BP-MVSNet: Belief-Propagation-Layers for Multi-View-Stereo
We therefore show how we can calculate a normalization based on the expected 3D error, which we can then use to normalize the label jumps in the CRF.
Joint Graph-based Depth Refinement and Normal Estimation
Depth estimation is an essential component in understanding the 3D geometry of a scene, with numerous applications in urban and indoor settings.
DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction
Deep Neural Networks (DNNs) have the potential to improve the quality of image-based 3D reconstructions.
