AI RESEARCH
TornadoNet: Real-Time Building Damage Detection with Ordinal Supervision
arXiv CS.CV
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ArXi:2603.11557v1 Announce Type: new We present TornadoNet, a comprehensive benchmark for automated street-level building damage assessment evaluating how modern real-time object detection architectures and ordinal-aware supervision strategies perform under realistic post-disaster conditions. TornadoNet provides the first controlled benchmark nstrating how architectural design and loss formulation jointly influence multi-level damage detection from street-view imagery, delivering methodological insights and deployable tools for disaster response.