arXiv:1609.05257
공식 코드 · Papers with Code
A convolutional approach to reflection symmetry
원문 초록
We present a convolutional approach to reflection symmetry detection in 2D. Our model, built on the products of complex-valued wavelet convolutions, simplifies previous edge-based pairwise methods. Being parameter-centered, as opposed to feature-centered, it has certain computational advantages when the object sizes are known a priori, as demonstrated in an ellipse detection application. The method outperforms the best-performing algorithm on the CVPR 2013 Symmetry Detection Competition Database in the single-symmetry case. Code and a new database for 2D symmetry detection is available.
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Reflection and Rotation Symmetry Detection via Equivariant Learning
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images
Data Augmentation through Expert-guided Symmetry Detection to Improve Performance in Offline Reinforcement Learning
토론
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