Image Geolocalization

Image geolocalization aims to determine the geographic location where a photograph was taken, using only the image's visual content. Current research heavily utilizes deep learning models, particularly vision transformers and large vision-language models (LVLMs), often incorporating multi-modal data (e.g., satellite imagery, maps) and employing techniques like ensemble methods and hierarchical attention mechanisms to improve accuracy, especially in under-represented regions. This field is crucial for various applications, including digital forensics, environmental monitoring, and combating human trafficking, as accurate geolocation can provide critical context and evidence. The development of robust and generalizable models that perform well across diverse geographic locations and image types remains a key focus.