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NeurIPS 2024Spotlight PosterAccept (Spotlight)

Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era

Yohann PERRON, Vladyslav Sydorov, Adam P. Wijker, Damian Evans, Christophe Pottier, Loic Landrieu

Ecole Nationale des Ponts et Chausees · French School of Asian Studies (EFEO) · École française d'Extrême-Orient · École française d'Extrême-Orient (EFEO) · Ecole française d'Extrême-Orient

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摘要

Airborne Laser Scanning (ALS) technology has transformed modern archaeology by unveiling hidden landscapes beneath dense vegetation. However, the lack of expert-annotated, open-access resources has hindered the analysis of ALS data using advanced deep learning techniques. We address this limitation with Archaeoscape (available at https://archaeoscape.ai/data/2024), a novel large-scale archaeological ALS dataset spanning 888 km² in Cambodia with 31,141 annotated archaeological features from the Angkorian period. Archaeoscape is over four times larger than comparable datasets, and the first ALS archaeology resource with open-access data, annotations, and models.We benchmark several recent segmentation models to demonstrate the benefits of modern vision techniques for this problem and highlight the unique challenges of discovering subtle human-made structures under dense jungle canopies. By making Archaeoscape available in open access, we hope to bridge the gap between traditional archaeology and modern computer vision methods.