English(EN) FD-CanKD: Frequency-Decoupled Cross-Attention Distillation as a Refinement Prior for Compact Object Detectors

新的FD-CanKD框架提高了紧凑型目标检测器的准确性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-20 04:00

研究人员开发了一个名为FD-CanKD的新知识蒸馏框架，旨在提高紧凑型目标检测器的准确性，同时不增加其参数数量。该方法在多个层面将知识从较大的教师模型转移到较小的学生模型：预测、上下文和频率。在COCO数据集上的实验表明，FD-CanKD可以显著提升紧凑型检测器的性能，在微调后达到48.87 mAP50:95的平均精度均值，而学生模型在训练后尺寸保持不变。 AI

影响这项研究可能为资源受限环境带来更高效、更准确的目标检测模型。

排序理由该集群包含一篇详细介绍新目标检测方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍新目标检测方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · YoungJae Cheong, Jhonghyun An · 2026-08-20 04:00

FD-CanKD：频率解耦交叉注意力蒸馏作为紧凑型目标检测器的精炼先验

arXiv:2608.18590v1 Announce Type: new Abstract: Compact object detectors are suitable for resource-constrained visual perception, but their limited representation capacity creates an accuracy gap relative to large models. Conventional detector distillation often relies on predict…

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FD-CanKD：频率解耦交叉注意力蒸馏作为紧凑型目标检测器的精炼先验

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