PULSE: PERSISTENT UTILIZATION OF LIMITED SUPPORT EVIDENCE FOR CROSS-DOMAIN FEW-SHOT OBJECT DETECTION

Cross-domain few-shot object detection (CD-FSOD) aims to localize and clas- sify novel objects in unseen domains using only a few annotated target examples. However, fine-tuning-based adaptation can suffer from support underutilization: while limited target examples are used to update detector parameters during fine- tuning, the same target evidence need not remain directly accessible when query predictions are scored. To address this limitation, this work introduces Persis- tent Utilization of Limited Support Evidence (PULSE), a novel framework that continuously leverages annotated target appearances during prediction scoring. Specifically, after target-domain adaptation, PULSE caches multi-view support features in a frozen evidence bank. SSCA is then proposed to align these cached support representations with current query features and measure their support– query agreement. Based on this agreement, SSCA integrates a gated residual correction into the detector’s base class logits, rewarding predictions that are consistent with the observed target support while suppressing confident yet un- supported detections. Importantly, this refinement operates only on classification scores and leaves predicted bounding box coordinates unchanged. Extensive ex- periments across six CD-FSOD benchmarks demonstrate the effectiveness of the proposed approach. PULSE achieves state-of-the-art mean AP under different shot settings. Furthermore, PULSE outperforms the corresponding FT-FSOD results in 16 of the 18 domain–shot settings and matches them in the remaining two, indicating that prediction-time support consultation provides a complementary signal to conventional parameter adaptation.