3 accepted papers
As AI generative models evolve, face swap technology has become increasingly accessible, raising concerns over potential misuse. Celebrities may be manipulated without consent, and ordinary individuals may fall victim to identity fraud. To address these threats, we propose Secure Swap, a method that…
Current Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities in understanding multimodal data, but their potential remains underexplored for deepfake detection due to the misalignment of their knowledge and forensics patterns. To this end, we present a novel framework that…
Existing solutions to zero-shot text classification either conduct prompting with pre-trained language models, which is sensitive to the choices of templates, or rely on large-scale annotated data of relevant tasks for meta-tuning. In this work, we propose a new paradigm based on self-supervised lea…