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COXNet: Cross-Layer Fusion with Adaptive Alignment and Scale Integration for RGBT Tiny Object Detection

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学术前沿 5.3 分 — 中等质量:常规学术论文,有适度参考价值
原文: cs.AI updates on arXiv.org

评分 5.3 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-14

评分依据:中等质量:常规学术论文,有适度参考价值

COXNet: Cross-Layer Fusion with Adaptive Alignment and Scale Integration for RGBT Tiny Object Detection

arXiv:2508.09533v2 Announce Type: replace-cross Abstract: Detecting tiny objects in multimodal Red-Green-Blue-Thermal (RGBT) imagery is a critical challenge in computer vision, particularly in surveillance, search and rescue, and autonomous navigation. Drone-based scenarios exacerbate these challenges due to spatial misalignment, low-light conditions, occlusion, and cluttered backgrounds. Current methods struggle to leverage the complementary information between visible and thermal modalities…