Reflection Symmetry

Reflection symmetry, a fundamental concept in mathematics and physics, is increasingly central to advancements in machine learning and image processing. Current research focuses on developing algorithms and model architectures that either leverage or explicitly account for reflectional invariance in data, for example, by incorporating it into neural network designs or using it to improve the accuracy of symmetry detection. This work is driven by the need to improve the robustness and efficiency of machine learning models, particularly in applications involving point cloud analysis and image restoration, where reflection symmetry is prevalent. The resulting improvements in data analysis and image processing have significant implications for diverse fields, including cultural heritage studies and 3D modeling.