1 citations · 1 across the 7 of their papers we have counts for
9 papers · 1 filter
Deep Residual Injection for Full-Spectrum Forensic Signal Perception in Multimodal Large Language Models
Kaiqing Lin, Zhiyuan Yan, Ruoxin Chen +8
Multimodal large language models (MLLMs) have been increasingly adopted in forensics for their robust semantic understanding. As AI-generated images become realistic, semantic-leve…
Disentangling Hallucinations: Orthogonal Semantic Projection for Robust Interpretability
Emirhan Bilgiç, Baptiste Caramiaux, Zhi Yan +1
As Vision-Language Models are increasingly deployed in safety-critical applications, the trustworthiness of their explanations becomes crucial. Explainable AI (XAI) methods for Vis…
FakeVLM-R1: Internalizing Physical Laws via CoT for Synthetic Image Detection
Leqi Zhu, Junyan Ye, Kaiqing Lin +3
The development of generative artificial intelligence technologies has propelled the visual realism of synthetic images to an unprecedented level. Although current interpretable de…
Towards Policy-Adaptive Image Guardrail: Benchmark and Method
Caiyong Piao, Zhiyuan Yan, Haoming Xu +4
Accurate rejection of sensitive or harmful visual content, i.e., harmful image guardrail, is critical in many application scenarios. This task must continuously adapt to the evolvi…
MIRROR: Manifold Ideal Reference ReconstructOR for Generalizable AI-Generated Image Detection
Ruiqi Liu, Manni Cui, Ziheng Qin +12
High-fidelity generative models have narrowed the perceptual gap between synthetic and real images, posing serious threats to media security. Most existing AI-generated image (AIGI…
Your One-Stop Solution for AI-Generated Video Detection
Long Ma, Zihao Xue, Yan Wang +6
Recent advances in generative modeling can create remarkably realistic synthetic videos, making it increasingly difficult for humans to distinguish them from real ones and necessit…
Beyond Artifacts: Real-Centric Envelope Modeling for Reliable AI-Generated Image Detection
Ruiqi Liu, Yi Han, Zhengbo Zhang +9
The rapid progress of generative models has intensified the need for reliable and robust detection under real-world conditions. However, existing detectors often overfit to generat…
From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakes
Long Ma, Zhiyuan Yan, Jin Xu +5
Detecting deepfakes has been an increasingly important topic, especially given the rapid development of AI generation techniques. In this paper, we ask: How can we build a universa…
Detecting AI-Generated Video via Frame Consistency
Long Ma, Zhiyuan Yan, Qinglang Guo +3
The escalating quality of video generated by advanced video generation methods results in new security challenges, while there have been few relevant research efforts: 1) There is…