13 papers with code • 1 benchmarks • 4 datasets
These leaderboards are used to track progress in Symmetry Detection
Most implemented papers
DeepFlux for Skeletons in the Wild
In the present article, we depart from this strategy by training a CNN to predict a two-dimensional vector field, which maps each scene point to a candidate skeleton pixel, in the spirit of flux-based skeletonization algorithms.
Symmetry Detection of Occluded Point Cloud Using Deep Learning
Symmetry detection has been a classical problem in computer graphics, many of which using traditional geometric methods.
A convolutional approach to reflection symmetry
We present a convolutional approach to reflection symmetry detection in 2D.
SRN: Side-output Residual Network for Object Symmetry Detection in the Wild
By stacking RUs in a deep-to-shallow manner, SRN exploits the 'flow' of errors among multiple scales to ease the problems of fitting complex outputs with limited layers, suppressing the complex backgrounds, and effectively matching object symmetry of different scales.
Wavelet-based Reflection Symmetry Detection via Textural and Color Histograms
Symmetry is one of the significant visual properties inside an image plane, to identify the geometrically balanced structures through real-world objects.
SRN: Side-output Residual Network for Object Reflection Symmetry Detection and Beyond
The end-to-end deep learning approach, referred to as a side-output residual network (SRN), leverages the output residual units (RUs) to fit the errors between the object ground-truth symmetry and the side-outputs of multiple stages.
Symmetry Detection and Classification in Drawings of Graphs
Finally, we make available a collection of images of graph drawings with specific symmetric features that can be used in machine learning systems for training, testing and validation purposes.
PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models
In this paper, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape.
Data Augmentation through Expert-guided Symmetry Detection to Improve Performance in Offline Reinforcement Learning
Offline estimation of the dynamical model of a Markov Decision Process (MDP) is a non-trivial task that greatly depends on the data available in the learning phase.
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images
We demonstrate and analyze the performance of the extended algorithm to detect localised symmetries and the machine learning model to classify rotational symmetries.