5 papers
Video as Natural Augmentation: Towards Unified AI-Generated Image and Video Detection
Zhengcen Li, Chenyang Jiang, Liangxu Su +4
AI-generated content (AIGC) is rapidly improving, creating an urgent need for detectors that generalize across data sources, deployment pipelines, and visual modalities. A strongly…
Preserving Forgery Artifacts: AI-Generated Video Detection at Native Scale
Zhengcen Li, Chenyang Jiang, Hang Zhao +7
The rapid advancement of video generation models has enabled the creation of highly realistic synthetic media, raising significant societal concerns regarding the spread of misinfo…
Multimodal Dataset Distillation via Phased Teacher Models
Shengbin Guo, Hang Zhao, Senqiao Yang +5
Multimodal dataset distillation aims to construct compact synthetic datasets that enable efficient compression and knowledge transfer from large-scale image-text data. However, exi…
Parameterizing Dataset Distillation via Gaussian Splatting
Chenyang Jiang, Zhengcen Li, Hang Zhao +3
Dataset distillation aims to compress training data while preserving training-aware knowledge, alleviating the reliance on large-scale datasets in modern model training. Dataset pa…
Rectifying Soft-Label Entangled Bias in Long-Tailed Dataset Distillation
Chenyang Jiang, Hang Zhao, Xinyu Zhang +4
Dataset distillation compresses large-scale datasets into compact, highly informative synthetic data, significantly reducing storage and training costs. However, existing research…