5 papers
V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors
Shichao Kan, Chengpeng Hong, Jingtong Dou +8
As generated videos become increasingly realistic, reliable video forgery detection is increasingly important. Existing studies typically optimize and use video forgery detectors a…
Beyond Surface Artifacts: Capturing Shared Latent Forgery Knowledge Across Modalities
Jingtong Dou, Chuancheng Shi, Jian Wang +3
As generative artificial intelligence evolves, deepfake attacks have escalated from single-modality manipulations to complex, multimodal threats. Existing forensic techniques face…
DNA: Uncovering Universal Latent Forgery Knowledge
Jingtong Dou, Chuancheng Shi, Yemin Wang +6
As generative AI achieves hyper-realism, superficial artifact detection has become obsolete. While prevailing methods rely on resource-intensive fine-tuning of black-box backbones,…
HarmoniAD: Harmonizing Local Structures and Global Semantics for Anomaly Detection
Naiqi Zhang, Chuancheng Shi, Jingtong Dou +3
Anomaly detection is crucial in industrial product quality inspection. Failing to detect tiny defects often leads to serious consequences. Existing methods face a structure-semanti…
Where Culture Fades: Revealing the Cultural Gap in Text-to-Image Generation
Chuancheng Shi, Shangze Li, Shiming Guo +9
Multilingual text-to-image (T2I) models have advanced rapidly in terms of visual realism and semantic alignment, and are now widely utilized. Yet outputs vary across cultural conte…