Generalizable Synthetic Image Detection via Language-Guided Contrastive Learning

Summary

Researchers propose a synthetic image detection method that uses language-guided contrastive learning. Training images receive carefully designed textual labels, and a joint visual-language contrastive objective learns a forensic feature space. The method generalizes better to unseen image generation models and outperforms state-of-the-art competitors across four datasets.