Semantic Scholar Open Access 2024 9 sitasi

EarthLoc: Astronaut Photography Localization by Indexing Earth from Space

G. Berton Alex Stoken Barbara Caputo Carlo Masone

Abstrak

Astronaut photography, spanning six decades of human spaceflight, presents a unique Earth observations dataset with immense value for both scientific research and disaster response. Despite their significance, accurately localizing the geographical extent of these images, which is crucial for effective utilization, poses substantial challenges. Cur-rent, manual localization efforts are time-consuming, mo-tivating the need for automated solutions. We propose a novel approach - leveraging image retrieval - to address this challenge efficiently. We introduce innovative training techniques which contribute to the development of a high-performance model, EarthLoc. We develop six evaluation datasets and perform a comprehensive benchmark comparing EarthLoc to existing methods, showcasing its superior efficiency and accuracy. Our approach marks a signifi-cant advancement in automating the localization of astro-naut photography, which will help bridge a critical gap in Earth observations data. Code and datasets are available at https://github.com/gmberton/EarthLoc.

Topik & Kata Kunci

Penulis (4)

G

G. Berton

A

Alex Stoken

B

Barbara Caputo

C

Carlo Masone

Format Sitasi

Berton, G., Stoken, A., Caputo, B., Masone, C. (2024). EarthLoc: Astronaut Photography Localization by Indexing Earth from Space. https://doi.org/10.1109/CVPR52733.2024.01212

Akses Cepat

Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.1109/CVPR52733.2024.01212
Akses
Open Access ✓