1 citations · 1 across the 5 of their papers we have counts for
5 papers
Consolidating Diffusion-Generated Video Detection with Unified Multimodal Forgery Learning
Xiaohong Liu, Xiufeng Song, Huayu Zheng +3
The proliferation of videos generated by diffusion models has raised increasing concerns about information security, highlighting the urgent need for reliable detection of syntheti…
A Mutil-conditional Diffusion Transformer for Versatile Seismic Wave Generation
Longfei Duan, Zicheng Zhang, Lianqing Zhou +4
Seismic wave generation creates labeled waveform datasets for source parameter inversion, subsurface analysis, and, notably, training artificial intelligence seismology models. Tra…
On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection
Xiufeng Song, Xiao Guo, Jiache Zhang +5
Large numbers of synthesized videos from diffusion models pose threats to information security and authenticity, leading to an increasing demand for generated content detection. Ho…
G-Refine: A General Quality Refiner for Text-to-Image Generation
Chunyi Li, Haoning Wu, Hongkun Hao +7
With the evolution of Text-to-Image (T2I) models, the quality defects of AI-Generated Images (AIGIs) pose a significant barrier to their widespread adoption. In terms of both perce…
Q-Refine: A Perceptual Quality Refiner for AI-Generated Image
Chunyi Li, Haoning Wu, Zicheng Zhang +7
With the rapid evolution of the Text-to-Image (T2I) model in recent years, their unsatisfactory generation result has become a challenge. However, uniformly refining AI-Generated I…