Stereo Dataset

Stereo datasets are collections of paired images taken from slightly different viewpoints, crucial for developing and evaluating algorithms that estimate depth (stereo matching). Current research focuses on improving the accuracy and efficiency of these algorithms, employing deep learning models (e.g., transformers, convolutional neural networks) and exploring both supervised and unsupervised learning approaches. The availability of diverse and high-quality stereo datasets, including those from challenging real-world scenarios (e.g., adverse weather, underwater environments), is critical for advancing 3D scene reconstruction and enabling applications in robotics, autonomous driving, and remote sensing.