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๐ŸŒ Earth Science

๐Ÿ“ท CVPR2025 ยท 1 paper notes

๐Ÿ“Œ Same area in other venues: ๐Ÿ“ท CVPR2026 (2) ยท ๐Ÿ”ฌ ICLR2026 (7) ยท ๐Ÿงช ICML2026 (2) ยท ๐Ÿค– AAAI2026 (2) ยท ๐Ÿง  NeurIPS2025 (6) ยท ๐ŸŽž๏ธ ECCV2024 (1)

GeoChemAD: Benchmarking Unsupervised Geochemical Anomaly Detection for Mineral Exploration

This paper proposes the GeoChemAD open-source benchmark dataset (comprising 8 subsets covering multiple regions, sampling sources, and target elements) and the GeoChemFormer framework. By employing spatial context self-supervised pre-training and elemental dependency modeling, it achieves unsupervised geochemical anomaly detection and obtains state-of-the-art AUC across all subsets.