Search Results for author: Emanuele Santellani

Found 3 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

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