๐ Earth Science¶
๐ท CVPR2025 ยท 1 paper notes
๐ Same area in other venues: ๐ท CVPR2026 (2) ยท ๐ฌ ICLR2026 (7) ยท ๐งช ICML2026 (2) ยท ๐ค AAAI2026 (2) ยท ๐ง NeurIPS2025 (6) ยท ๐๏ธ ECCV2024 (1)
- GeoChemAD: Benchmarking Unsupervised Geochemical Anomaly Detection for Mineral Exploration
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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.