基于张量化锚框引导的可扩展多视图子空间聚类
Scalable Multi-View Subspace Clustering with Tensorized Anchor Guidance
把跨视图锚框堆成三阶张量并用张量 Schatten p-范数约束，显式建模跨视图低秩结构，这一正则与样本数无关，可直接迁移到大规模视觉检索/聚类中的锚框图构建与跨模态一致性建模。
原文依据 we construct a third-order anchor tensor from view-specific anchors in a low-dimensional latent space
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论近年来，基于锚框的多视图聚类方法因在处理大规模数据集上的有效性而受到广泛关注。这类方法的性能高度依赖于锚框质量。然而，现有方法忽略了跨视图锚框之间的交互关系，无法有效发现和利用一致性与互补性信息，导致锚框表示含有噪声或次优。本文提出一种新的基于张量化锚框引导的可扩展多视图子空间聚类方法，通过直接耦合各视图的锚框来提升聚类性能。具体而言，我们在低维潜变量空间中由各视图特定的锚框构建三阶锚框张量。通过对锚框张量施加张量 Schatten p-范数约束，我们能够显式刻画跨视图低秩结构，并联合利用锚框之间的一致性与互补性信息。此外，张量化锚框正则项与样本数量无关，从而降低了时间与空间复杂度。在七个数据集上的实验结果表明，与最优的大规模多视图聚类方法相比，SMVS-TAG 具有更优的有效性与稳定性。代码已开源：https://github.com/Jiamiao2024/SMVS-TAG。
英文原文摘要 1326 字符
Anchor-based multi-view clustering methods have gained significant attention for their effectiveness in handling large-scale datasets in recent years. The performance of these methods is highly dependent on anchor quality. However, current methods neglect the interactive relationships among cross-view anchors, failing to effectively discover and exploit consistent and complementary information, leading to noisy or suboptimal anchor representations. In this paper, we propose a novel scalable multi-view subspace clustering method with tensorized anchor guidance, which directly couples anchors across views to improve clustering performance. Specifically, we construct a third-order anchor tensor from view-specific anchors in a low-dimensional latent space. By imposing a tensor Schatten p-norm constraint on the anchor tensor, we can explicitly capture cross-view low-rank structure and jointly exploit consistent and complementary information among anchors. Moreover, the tensorized anchor regularizer is independent of the number of samples, which reduces both time and space complexity. Experimental results on seven datasets demonstrate that SMVS-TAG achieves superior effectiveness and stability compared to state-of-the-art large-scale MVC methods. Our code is available at https://github.com/Jiamiao2024/SMVS-TAG.