The flexibility of the HR-APR framework allows for the integration of other sensor data to improve camera relocalization accuracy and robustness. To incorporate depth information, depth estimation networks such as monocular depth estimation models could be integrated into the feature extraction process to provide depth-aware feature embeddings. Inertial sensor data, such as gyroscope and accelerometer readings, could be fused with visual data using sensor fusion techniques like Kalman filters or particle filters to enhance pose estimation accuracy, especially in dynamic environments. By combining multiple modalities of sensor data, the HR-APR framework can offer a more comprehensive and reliable camera relocalization solution.