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Found 4 papers, 2 papers with code
Learning Rotation-Equivariant Features for Visual Correspondence
The resultant features and their orientations are further processed by group aligning, a novel invariant mapping technique that shifts the group-equivariant features by their orientations along the group dimension.
Self-Supervised Equivariant Learning for Oriented Keypoint Detection
Detecting robust keypoints from an image is an integral part of many computer vision problems, and the characteristic orientation and scale of keypoints play an important role for keypoint description and matching.
Reflection and Rotation Symmetry Detection via Equivariant Learning
The inherent challenge of detecting symmetries stems from arbitrary orientations of symmetry patterns; a reflection symmetry mirrors itself against an axis with a specific orientation while a rotation symmetry matches its rotated copy with a specific orientation.
Rotation-Equivariant Keypoint Detection
Therefore, we propose a rotation-invariant keypoint detection method using rotation-equivariant CNNs.
