Enhancing Deformable Local Features by Jointly Learning to Detect and Describe Keypoints

Author:

Potje Guilherme1,Cadar Felipe1,Araujo André2,Martins Renato3,Nascimento Erickson R.1

Affiliation:

1. Universidade Federal de Minas Gerais

2. Google Research

3. Université de Bourgogne

Funder

CAPES

CNPq

FAPEMIG

Google

CNRS

Publisher

IEEE

Reference42 articles.

1. Key. net: Keypoint detection by handcrafted and learned cnn filters;laguna;ArXiv Preprint,2019

2. SOSNet: Second Order Similarity Regularization for Local Descriptor Learning

3. Image matching across wide baselines: From paper to practice;jin;International Journal of Computer Vision,2020

4. L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space

5. Geodesc: Learning local descriptors by integrating geometry constraints;luo;Proceedings of the European Conference on Computer Vision (ECCV),0

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1. Mountainous road vector data update method based on matching point pair grouping;International Journal of Remote Sensing;2024-05-20

2. RIDE: Self-Supervised Learning of Rotation-Equivariant Keypoint Detection and Invariant Description for Endoscopy;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Tracking and mapping in medical computer vision: A review;Medical Image Analysis;2024-05

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