Revealing Artifacts via Noise Amplification: A Novel Perspective for AI-Generated Video Detection
With the rapid advancement of video generation models, distinguishing between AI-generated and authentic videos has emerged as a challenging endeavor. The majority of existing research endeavors concentrate on the development of detectors for identifying samples generated by generative adversarial networks. Nevertheless, the detection of AI-generated videos, particularly those produced by text-to-video models, still remains an uncharted territory. Although state-of-the-art text-to-video models can generate realistic visual content similar to real videos, they fall short of generating the details of the images and the changes in details within the videos. Inspired by this, we address AI-ge...
| Authors | Renxi Cheng, Jie Gui, Hongsong Wang |
|---|---|
| Primary category | cs.CV |
| Published | 15 June 2026 |
| Last updated at source | 15 June 2026 |
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