3D Fa\c{c}ade Detail

3D facade detail reconstruction aims to create highly accurate three-dimensional models of building exteriors, capturing fine-grained features beyond simple geometric shapes. Current research focuses on overcoming challenges like occlusions and noise in point cloud data using deep learning methods, such as attention-based networks and B-spline active surfaces, often combined with techniques like point completion and Bag-of-Words approaches for improved feature identification. These advancements are crucial for applications ranging from creating digital twins for urban planning to supporting autonomous driving systems and facilitating more precise architectural analysis. The development of robust and efficient methods for facade detail reconstruction is driving progress in both computer vision and related fields.