Los Angeles
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Price Level | Los Angeles | Accuracy0.684 | 28 | |
| Busyness | Los Angeles | MAE0.136 | 28 | |
| Visit Intent | Los Angeles | F1 Score36.8 | 28 | |
| Permanent Closure | Los Angeles | F1 Score78.6 | 28 | |
| Open Hours | Los Angeles | F1 Score63.7 | 28 | |
| Hyperspectral Anomaly Detection | Los Angeles II | Average Running Time (s)0.0477 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles I | Average Running Time (s)0.0455 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles II (Case 5) | AUC (PD vs PF)0.9802 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles I Case 5 | AUC (PD, PF)99.35 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles II (Case 1) | AUC (PD vs PF)0.989 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles I (Case 1) | AUC (PD vs PF)99.66 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles II (test) | AUC (PD vs PF)0.9879 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles I (test) | AUC (PD, PF)0.9961 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles II (Case 2) | AUC (PD vs PF)0.9845 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles I (Case 2) | AUC (ROC)0.9967 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles Mixed Noise Condition II (Case 4) | AUC (PD vs PF)0.9881 | 14 | |
| Hyperspectral Anomaly Detection | Los Angeles I Mixed Noise Condition (Case 4) | AUC (PD vs PF)99.66 | 14 | |
| Urban Morphology Generation | Los Angeles | FID28.56 | 2 |
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