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Found 7 papers, 1 papers with code
S-TREK: Sequential Translation and Rotation Equivariant Keypoints for local feature extraction
In this work we introduce S-TREK, a novel local feature extractor that combines a deep keypoint detector, which is both translation and rotation equivariant by design, with a lightweight deep descriptor extractor.
DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo
We denote our method DELS-MVS: Deep Epipolar Line Search Multi-View Stereo.
MD-Net: Multi-Detector for Local Feature Extraction
In order to lower the computational cost of the matching phase, we propose a deep feature extraction network capable of detecting a predefined number of complementary sets of keypoints at each image.
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.
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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.
Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems
It has been proposed by many researchers that combining deep neural networks with graphical models can create more efficient and better regularized composite models.
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.
