A case for using rotation invariant features in state of the art feature
matchers

A case for using rotation invariant features in state of the art feature matchers

21 April 2022

Georg Bökman

Papers citing "A case for using rotation invariant features in state of the art feature matchers"

6 / 6 papers shown

Title
Geolocating Earth Imagery from ISS: Integrating Machine Learning with Astronaut Photography for Enhanced Geographic Mapping Vedika Srivastava Hemant Kumar Singh Jaisal Singh 28 0 0 29 Apr 2025
To Match or Not to Match: Revisiting Image Matching for Reliable Visual Place Recognition Davide Sferrazza Gabriele Berton Gabriele Trivigno Carlo Masone 34 0 0 08 Apr 2025
Investigating how ReLU-networks encode symmetries Georg Bökman Fredrik Kahl 29 6 0 26 May 2023
RoMa: Robust Dense Feature Matching Johan Edstedt Qiyu Sun Georg Bökman Maarten Wadenback M. Felsberg 3DV 36 92 0 24 May 2023
In Search of Projectively Equivariant Networks Georg Bökman Axel Flinth Fredrik Kahl 44 0 0 29 Sep 2022
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,106 0 27 Apr 2021