Coarse to Fine Fusion

Coarse-to-fine fusion is a data processing strategy that integrates information from multiple sources or modalities, progressively refining the representation from a coarse initial estimate to a detailed final output. Current research focuses on applying this approach to diverse fields, including object detection (using event cameras, RGB-IR images), and scientific data compression (combining machine learning with traditional methods). This technique improves robustness and accuracy in various applications by leveraging complementary information at different levels of detail, leading to more efficient and effective data analysis and processing.