为警方开发的刀具图像检索系统，精准匹配细粒度刀具特征。
KnifeHunter: Structured Local Representation Learning for Fine-Grained Knife Image Retrieval in Law Enforcement
- 用局部特征与全局上下文融合的紧凑模型，提升刀具识别精度。
- 在中等难度测试中达到88.0% mAP，实际执法中单查询准确率达99.2%。
- 专为警务场景设计，适合刑事侦查与证据溯源使用。
刀具暴力是重大公共安全挑战，警方亟需可扩展的刀具识别、情报分析与溯源工具。人工视觉比对耗时且难规模化。我们提出KnifeHunter，一个与英国警方合作开发的端到端法医刀具图像检索系统。该工作构建了包含543类刀具、共25,843张图像的KnifeHunter数据集，涵盖警用证据、零售目录和边境查获样本，配有结构化元数据、中/难评估协议及大规模干扰项测试。我们进一步提出CoRe-Net，一种结合全局上下文与空间局部判别性特征的紧凑单描述符检索架构。CoRe-Net引入结构化互补表征学习（SCRL）将局部证据组织为原型驱动表示，并通过双向互惠融合（BDRF）实现残差投影与门控局部到全局注入。采用EVA02-Base骨干网络与余弦相似度检索，在中等协议下达88.0% mAP和86.7% mP@10，干扰条件下达85.1% mAP和83.8% mP@10。KnifeHunter自2023至2025年在英国警方行动中部署，现场查询实现99.2% mP@1。结果表明该框架在实际警务环境中具备高效、可靠的细粒度刀具匹配能力。
原文摘要 · Abstract (English)
Knife-enabled violence presents a major public safety challenge, and law enforcement agencies require scalable tools for catalogue-level knife identification, intelligence analysis, and source attribution. Manual visual comparison is specialist, time-consuming, and difficult to scale under operational imaging conditions. We introduce KnifeHunter, an end-to-end forensic knife image retrieval system developed with UK law enforcement. The work contributes the KnifeHunter dataset, comprising 25,843 images across 543 knife classes from police evidence, retail catalogues, and border-force seizures, with structured metadata, Medium/Hard evaluation protocols, and large-scale distractor evaluation. We further propose CoRe-Net, a compact single-descriptor retrieval architecture that combines global context with spatially localised discriminative evidence. CoRe-Net introduces Structured Complementary Representation Learning (SCRL) to organise local evidence into complementary prototype-based representations, and Bi-Directional Reciprocal Fusion (BDRF) to integrate global and local evidence through residual projection and gated local-to-global injection. Using an EVA02-Base backbone and cosine-similarity retrieval, CoRe-Net achieves 88.0% mAP and 86.7% mP@10 on the Medium protocol, and 85.1% mAP and 83.8% mP@10 under distractor conditions. KnifeHunter was deployed by UK police forces during Operation Sceptre deployments from 2023 to 2025, achieving 99.2% mP@1 on field queries. These results demonstrate a practical and effective multimedia retrieval framework for fine-grained forensic knife matching in operational law-enforcement settings.
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