Camera Fusion

Camera fusion integrates data from multiple cameras, or cameras with other sensors like radar or LiDAR, to improve perception and overcome individual sensor limitations. Current research emphasizes developing robust deep learning models, often employing transformer architectures or multi-task learning strategies, to effectively fuse data from diverse sources, such as wide-angle and telephoto cameras, or cameras with radar, addressing challenges like data synthesis, sensor misalignment, and occlusion. This work is crucial for advancing applications in autonomous driving, mobile photography, and other fields requiring high-quality, reliable visual information, particularly in challenging environments.