CoPS: Conditional Prompt Synthesis for Zero-Shot Anomaly Detection

Researchers have introduced Conditional Prompt Synthesis (CoPS), a framework that enhances zero-shot anomaly detection by dynamically generating prompts based on visual features, improving model performance across diverse datasets. This innovation addresses limitations in existing prompt learning methods, offering better generalization and reducing overfitting risks for developers working with large vision-language models.

Read the full article at arXiv cs.CV (Vision)

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