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Domain shift-robust object detection with GenAI image editing

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Object detectors often degrade under domain shifts such as changes in lighting, weather, or occlusion. These shifts alter object appearance and expose a reliance on visual shortcuts learned from the training distribution that do not generalize across domains. Acquiring sufficient real-world samples to capture such domain variation is particularly difficult in specialized, low-data settings. Recent advances in diffusion-based generative image editing have shown promise for improving the in-domain performance of object detectors through synthetic data augmentation. However, their potential to im

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Evidence & attribution

First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.