View Correspondence

View correspondence, the task of identifying matching points or features across multiple views of the same scene or object, is crucial for numerous computer vision applications. Current research focuses on robustly establishing these correspondences even in challenging scenarios like unaligned data, sparse views, or noisy measurements, employing techniques such as graph neural networks, transformer architectures, and probabilistic methods to improve accuracy and efficiency. These advancements are driving progress in 3D reconstruction, object tracking, cross-modal retrieval (e.g., image-text), and other areas requiring the integration of information from multiple perspectives, ultimately leading to more accurate and reliable computer vision systems.