Reconstruction Method

Reconstruction methods aim to create accurate 3D models from various input data, such as images, depth maps, and LiDAR point clouds. Current research focuses on improving the accuracy and efficiency of neural implicit representations, often employing techniques like ray bundles, geometry-guided ray augmentation, and convolutional networks to refine surface details and handle sparse or incomplete data. These advancements are significant for applications ranging from robotics and virtual reality to computer-aided design and cultural heritage preservation, enabling more realistic and detailed 3D scene modeling.