Using SigLIP retrieval to feed a Qwen2-VL or InternVL2 model with similar and dissimilar coordinates yields reported street-level accuracies of 23.2%, 17.1%, and 24.3% on IM2GPS, IM2GPS3k, and YFCC4k.
Autonomous smartphone-based wifi positioning system by using access points localization and crowdsourcing,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
REJECT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Street-Level Geolocalization Using Multimodal Large Language Models and Retrieval-Augmented Generation
Using SigLIP retrieval to feed a Qwen2-VL or InternVL2 model with similar and dissimilar coordinates yields reported street-level accuracies of 23.2%, 17.1%, and 24.3% on IM2GPS, IM2GPS3k, and YFCC4k.