Stereo Matching Algorithm

Stereo matching algorithms aim to reconstruct 3D scenes from pairs of 2D images by identifying corresponding pixels. Current research focuses on improving accuracy and robustness, particularly for challenging real-world scenarios, using deep learning architectures like convolutional neural networks and transformers, often incorporating geometric knowledge and uncertainty estimation. These advancements are crucial for applications such as autonomous navigation, robotics, and 3D modeling, driving progress in both computational efficiency and the handling of complex scenes.