1 citations · 1 across the 5 of their papers we have counts for
5 papers
VideoMarkBench: Benchmarking Robustness of Video Watermarking
Zhengyuan Jiang, Moyang Guo, Kecen Li +5
The rapid development of video generative models has led to a surge in highly realistic synthetic videos, raising ethical concerns related to disinformation and copyright infringem…
AI-generated Image Detection: Passive or Watermark?
Moyang Guo, Yuepeng Hu, Zhengyuan Jiang +4
While text-to-image models offer numerous benefits, they also pose significant societal risks. Detecting AI-generated images is crucial for mitigating these risks. Detection method…
Certifiably Robust Image Watermark
Zhengyuan Jiang, Moyang Guo, Yuepeng Hu +2
Generative AI raises many societal concerns such as boosting disinformation and propaganda campaigns. Watermarking AI-generated content is a key technology to address these concern…
Refusing Safe Prompts for Multi-modal Large Language Models
Zedian Shao, Hongbin Liu, Yuepeng Hu +1
Multimodal large language models (MLLMs) have become the cornerstone of today's generative AI ecosystem, sparking intense competition among tech giants and startups. In particular,…
Searching Priors Makes Text-to-Video Synthesis Better
Haoran Cheng, Liang Peng, Linxuan Xia +5
Significant advancements in video diffusion models have brought substantial progress to the field of text-to-video (T2V) synthesis. However, existing T2V synthesis model struggle t…