Learning Clustering-based Prototypes for Compositional Zero-shot Learning

• URL: http://arxiv.org/abs/2502.06501v1
• Date: Mon, 10 Feb 2025 14:20:01 GMT
• Title: Learning Clustering-based Prototypes for Compositional Zero-shot Learning
• Authors: Hongyu Qu, Jianan Wei, Xiangbo Shu, Wenguan Wang,
• Abstract summary: ClusPro is a robust clustering-based prototype mining framework for Compositional Zero-Shot Learning. It defines the conceptual boundaries of primitives through a set of diversified prototypes. ClusPro efficiently performs prototype clustering in a non-parametric fashion without the introduction of additional learnable parameters.
• Score: 56.57299428499455
• License:
• Abstract: Learning primitive (i.e., attribute and object) concepts from seen compositions is the primary challenge of Compositional Zero-Shot Learning (CZSL). Existing CZSL solutions typically rely on oversimplified data assumptions, e.g., modeling each primitive with a single centroid primitive representation, ignoring the natural diversities of the attribute (resp. object) when coupled with different objects (resp. attribute). In this work, we develop ClusPro, a robust clustering-based prototype mining framework for CZSL that defines the conceptual boundaries of primitives through a set of diversified prototypes. Specifically, ClusPro conducts within-primitive clustering on the embedding space for automatically discovering and dynamically updating prototypes. These representative prototypes are subsequently used to repaint a well-structured and independent primitive embedding space, ensuring intra-primitive separation and inter-primitive decorrelation through prototype-based contrastive learning and decorrelation learning. Moreover, ClusPro efficiently performs prototype clustering in a non-parametric fashion without the introduction of additional learnable parameters or computational budget during testing. Experiments on three benchmarks demonstrate ClusPro outperforms various top-leading CZSL solutions under both closed-world and open-world settings.

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