Cross-modal place recognition

Cross-modal place recognition is a subtask in the field of computer vision that aims to recognize and match the same location through data from different modalities (such as images, point clouds, etc.). The goal of this task is to build systems capable of perceiving the environment across modalities, thereby improving the positioning accuracy and robustness of robots and autonomous vehicles in complex environments. Its application value lies in enhancing multi-sensor fusion technology, improving scene understanding capabilities, and promoting autonomous navigation and environmental interaction of intelligent systems.