Search Results for author: Andreas Kuhn

Found 7 papers, 0 papers with code

S-TREK: Sequential Translation and Rotation Equivariant Keypoints for local feature extraction

no code implementations ICCV 2023 Emanuele Santellani, Christian Sormann, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer

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.

MD-Net: Multi-Detector for Local Feature Extraction

no code implementations10 Aug 2022 Emanuele Santellani, Christian Sormann, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer

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.

3D Reconstruction

BP-MVSNet: Belief-Propagation-Layers for Multi-View-Stereo

no code implementations23 Oct 2020 Christian Sormann, Patrick Knöbelreiter, Andreas Kuhn, Mattia Rossi, Thomas Pock, Friedrich Fraundorfer

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

no code implementations CVPR 2020 Mattia Rossi, Mireille El Gheche, Andreas Kuhn, Pascal Frossard

Depth estimation is an essential component in understanding the 3D geometry of a scene, with numerous applications in urban and indoor settings.

Depth Estimation

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