HMR-Net: Hierarchical Modular Routing for Cross-Domain Object Detection in Aerial Images
Despite advances in object detection, aerial imagery remains a challenging domain, as models often fail to generalize across variations in spatial resolution, scene composition, and semantic label coverage. Differences in geographic context, sensor characteristics, and object distributions across datasets limit the capacity of conventional models to learn consistent and transferable representations. Shared methods trained on such data tend to impose a unified representation across fundamentally different domains, resulting in poor performance on region-specific content and less flexibility when dealing with novel object categories. To address this, we propose a novel modular learning fram...
| Authors | Pourya Shamsolmoali, Masoumeh Zareapoor, Michael Felsberg et al. |
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| Primary category | cs.CV |
| Published | 20 April 2026 |
| Last updated at source | 15 June 2026 |
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