Web: https://www.reddit.com/r/computervision/comments/upftc3/a_case_for_using_rotation_invariant_features_in/

May 14, 2022, 12:03 p.m. | /u/moetsi_op

Computer Vision reddit.com

By: Georg Bokman and Fredrik Kahl: [https://arxiv.org/pdf/2204.10144.pdf](https://arxiv.org/pdf/2204.10144.pdf)

(Accepted to Image Matching Workshop CVPR 2022)


The aim of this paper is to demonstrate that a state of the art feature matcher (LoFTR) can be made more robust to rotations by simply replacing the backbone CNN with a steerable CNN which is equivariant to translations and image rotations. It is experimentally shown that this boost is obtained without reducing performance on ordinary illumination and viewpoint matching sequences.

art computervision features state

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC