When Satellite and Street Views Disagree: Cross-View Complementarity in Disaster Damage Assessment
Satellite and street-view imagery see different parts of a damaged building: roofs from above, facades and debris from the ground. Average accuracy hides whether fusion methods use this complementary evidence. We study the conflict cases, the samples on which independently trained single-view models disagree, as a diagnostic subset. On paired collections from the 2025 Eaton wildfire and Hurricanes Ian and Milton, conflicts make up 9.6-33.2% of the test data. Fusion improves conflict accuracy over either view, yet an oracle that selects the correct single view per conflict remains 0.19-0.32 above the best evaluated fusion method. A linear fusion gate over building-visibility features, cali...
| Authors | Yifan Yang, Lei Zou |
|---|---|
| Primary category | cs.CV |
| Published | 3 October 2026 |
| Last updated at source | 13 October 2026 |
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