Anti-I2V: Safeguarding your photos from malicious image-to-video generation
Advances in diffusion-based video generation models, while significantly improving human animation, poses threats of misuse through the creation of fake videos from a specific person's photo and text prompts. Recent efforts have focused on adversarial attacks that introduce crafted perturbations to protect images from diffusion-based models. However, most existing approaches target image generation, while relatively few explicitly address image-to-video diffusion models (VDMs), and most primarily focus on UNet-based architectures. Hence, their effectiveness against Diffusion Transformer (DiT) models remains largely under-explored, as these models demonstrate improved feature retention, an...
| Authors | Duc Vu, Anh Nguyen, Chi Tran et al. |
|---|---|
| Primary category | cs.CV |
| Published | 25 March 2026 |
| Last updated at source | 25 March 2026 |
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