面向少样本缺陷分类的双曲缺陷特征合成
Hyperbolic Defect Feature Synthesis for Few-Shot Defect Classification
把缺陷特征合成从欧氏空间搬到双曲空间，用少量双曲缺陷原型建模潜在缺陷分布，并用层级缺陷对比损失优化合成特征；做少样本工业缺陷分类、或需要建模层次结构的数据增强时，可复用这套双曲原型+对比损失的合成管线。
原文依据 we attempt to explore defect generation in hyperbolic space and propose a hyperbolic defect feature synthesis (HypDFS) method
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论缺陷合成作为解决少样本缺陷分类问题的核心技术，已在工业场景中被广泛采用。它通过构建数据增强流程，缓解了因数据稀缺而导致的模型泛化能力不足问题。近期，显式缺陷图像生成与隐式缺陷特征合成两类方法均取得了显著进展。然而，现有方法通常都在欧氏空间中实施。受欧氏空间平坦性的制约，难以合成包含复杂结构的缺陷数据。本文尝试在双曲空间中探索缺陷生成，提出了双曲缺陷特征合成（HypDFS）方法。该方法通过少量双曲缺陷原型对潜在缺陷分布进行建模，并进一步在双曲空间中利用层级缺陷对比损失优化合成缺陷特征，从而获得泛化性更好、更有利于下游少样本缺陷分类任务的缺陷表征。在少样本设置下于 MVTec-FS 基准和标准 MTD 数据集上进行的大量实验表明，所提出的 HypDFS 大幅超越欧氏基线，显示出双曲空间缺陷合成的良好前景。
英文原文摘要 1389 字符
Defect synthesis, as a core technology for addressing the problem of few-shot defect classification, has been widely adopted in industrial scenarios. It helps alleviate the problem of insufficient model generalization capability owing to data scarcity by establishing a data augmentation pipeline. Recently, remarkable progress has been achieved in both explicit defect image generation and implicit defect feature synthesis approaches. However, existing methods are always conducted in Euclidean space. Constrained by the flatness of Euclidean space, it is difficult to synthesize defect data containing complex structures. In this paper, we attempt to explore defect generation in hyperbolic space and propose a hyperbolic defect feature synthesis (HypDFS) method. By modeling the potential defect distribution via a small number of hyperbolic defect prototypes and further optimizing the synthetic defect features with the hierarchical defect contrastive loss in hyperbolic space, our HypDFS method can obtain a better generalized defect representation that is more conducive to downstream few-shot defect classification task. Extensive experiments on the MVTec-FS benchmark and standard MTD dataset under the few-shot settings demonstrate that the proposed HypDFS surpasses the Euclidean baseline by a large margin, showing promising prospects for defect synthesis in hyperbolic space.