Compositional Zero-Shot Learning
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Benchmarks
Most implemented
Learning Graph Embeddings for Open World Compositional Zero-Shot Learning
Open World Compositional Zero-Shot Learning
MSCI: Addressing CLIP's Inherent Limitations for Compositional Zero-Shot Learning
Learning Clustering-based Prototypes for Compositional Zero-shot Learning
Unified Framework for Open-World Compositional Zero-shot Learning
Papers
DIFFCZSL: Compositional Zero-Shot Learning Regularized by Diffusion Representations
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object compositions by leveraging knowledge of primitive concepts learned from seen compositions. Although recent works achieve impressive perfor…
Compositional Zero-Shot LearningProgressive Reasoning with Primitive Correction for Compositional Zero-Shot Learning
Compositional Zero-Shot Learning (CZSL) aims to combine known attributes and objects as primitives for recognizing previously unseen attribute-object pairs. Prior works either predict attributes and objects independently…
Compositional Zero-Shot LearningReinforcement LearningFlowComposer: Composable Flows for Compositional Zero-Shot Learning
Compositional zero-shot learning (CZSL) aims to recognize unseen attribute-object compositions by recombining primitives learned from seen pairs. Recent CZSL methods built on vision-language models (VLMs) typically adopt…
Compositional Zero-Shot Learningparameter-efficient fine-tuningStructure-aware Prompt Adaptation from Seen to Unseen for Open-Vocabulary Compositional Zero-Shot Learning
The goal of Open-Vocabulary Compositional Zero-Shot Learning (OV-CZSL) is to recognize attribute-object compositions in the open-vocabulary setting, where compositions of both seen and unseen attributes and objects are e…
Compositional Zero-Shot LearningWARM-CAT: Warm-Started Test-Time Comprehensive Knowledge Accumulation for Compositional Zero-Shot Learning
Compositional Zero-Shot Learning (CZSL) aims to recognize novel attribute-object compositions based on the knowledge learned from seen ones. Existing methods suffer from performance degradation caused by the distribution…
Compositional Zero-Shot LearningRepresentation Learning$\text{H}^2$em: Learning Hierarchical Hyperbolic Embeddings for Compositional Zero-Shot Learning
Compositional zero-shot learning (CZSL) aims to recognize unseen state-object compositions by generalizing from a training set of their primitives (state and object). Current methods often overlook the rich hierarchical …
Compositional Zero-Shot Learning