79 citations · 175 across the 30 of their papers we have counts for
5 papers · 1 filter
QE: Learning Discrete Distribution Discrepancy-aware Quantization Error for Autoregressive-Generated Image Detection
Yanran Zhang, Bingyao Yu, Yu Zheng +5
The emergence of visual autoregressive (AR) models has revolutionized image generation while presenting new challenges for synthetic image detection. Unlike previous GAN or diffusi…
Learning Counterfactually Decoupled Attention for Open-World Model Attribution
Yu Zheng, Boyang Gong, Fanye Kong +6
In this paper, we propose a Counterfactually Decoupled Attention Learning (CDAL) method for open-world model attribution. Existing methods rely on handcrafted design of region part…
GenWorld: Towards Detecting AI-generated Real-world Simulation Videos
Weiliang Chen, Wenzhao Zheng, Yu Zheng +4
The flourishing of video generation technologies has endangered the credibility of real-world information and intensified the demand for AI-generated video detectors. Despite some…
SpectralAR: Spectral Autoregressive Visual Generation
Yuanhui Huang, Weiliang Chen, Wenzhao Zheng +3
Autoregressive visual generation has garnered increasing attention due to its scalability and compatibility with other modalities compared with diffusion models. Most existing meth…
SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis
Weiliang Chen, Jiayi Bi, Yuanhui Huang +2
Generative models have shown great promise for novel view synthesis (NVS) by leveraging strong image generation priors. However, existing approaches typically follow a 2D inpaintin…