FocusOVD: Geometric and Contextual Feature Refinement for Open-Vocabulary Small-Object Detection

FocusOVD is an open‑vocabulary object detector that improves small‑object detection by refining geometric and contextual features without altering the frozen vision‑language model backbone. It introduces a Reweighted Cross‑scale Feature Fusion module to balance shallow and deep features, a Residual Pinwheel‑shaped Gated Convolution module to enhance local geometry in high‑resolution features, and a Residual Convolutional Gated Linear Unit module to suppress background activations and boost region‑of‑interest discriminability. Experiments on COCO‑OVD and LVIS‑OVD show that FocusOVD outperforms state‑of‑the‑art methods, achieving a novel‑category AP of 36.3% on COCO‑OVD and an overall AP of 33.7% on LVIS‑OVD.