16 citations · 20 across the 29 of their papers we have counts for
29 papers
HumanForge: A Human-Centric Deepfake Video Benchmark with Multi-Agent Forgery Rationales
Wenbo Xu, Zhimin Chen, Xiaojie Liang +3
Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, presenting unprecedented challenges to…
NullEdit: Stealthy Image Protection via VLM Condition Redirection
Weiyao Huang, Liqin Wang, Ziqi Sheng +1
Modern image editors combine vision-language models (VLMs) with diffusion transformer backbones to modify a single reference image according to instructions without fine-tuning. Th…
I2VShield: An Efficient Proactive Defense Framework against DiT-based Image-to-Video Models
Yimao Guo, Zuomin Qu, Wei Lu
The rapid advancement of video generation models has led to the increasing misuse of image-to-video (I2V) models. Although substantial progress has been made in detecting AI-genera…
CIEC: Coupling Implicit and Explicit Cues for Multimodal Weakly Supervised Manipulation Localization
Xinquan Yu, Wei Lu, Xiangyang Luo +1
To mitigate the threat of misinformation, multimodal manipulation localization has garnered growing attention. Consider that current methods rely on costly and time-consuming fine-…
Fake-HR1: Rethinking Reasoning of Vision Language Model for Synthetic Image Detection
Changjiang Jiang, Xinkuan Sha, Fengchang Yu +5
Recent studies have demonstrated that incorporating Chain-of-Thought (CoT) reasoning into the detection process can enhance a model's ability to detect synthetic images. However, e…
MARE: Multimodal Alignment and Reinforcement for Explainable Deepfake Detection via Vision-Language Models
Wenbo Xu, Wei Lu, Xiangyang Luo +1
Deepfake detection is a widely researched topic that is crucial for combating the spread of malicious content, with existing methods mainly modeling the problem as classification o…
Lossless Copyright Protection via Intrinsic Model Fingerprinting
Lingxiao Chen, Liqin Wang, Wei Lu +1
The exceptional performance of diffusion models establishes them as high-value intellectual property but exposes them to unauthorized replication. Existing protection methods eithe…
Safeguarding Facial Identity against Diffusion-based Face Swapping via Cascading Pathway Disruption
Liqin Wang, Qianyue Hu, Wei Lu +1
The rapid evolution of diffusion models has democratized face swapping but also raises concerns about privacy and identity security. Existing proactive defenses, often adapted from…
Mining Forgery Traces from Reconstruction Error: A Weakly Supervised Framework for Multimodal Deepfake Temporal Localization
Midou Guo, Qilin Yin, Wei Lu +1
Modern deepfakes have evolved into localized and intermittent manipulations that require fine-grained temporal localization to mitigate severe digital security risks. The prohibiti…
UniHetero: Could Generation Enhance Understanding for Vision-Language-Model at Large Data Scale?
Fengjiao Chen, Minhao Jing, Weitao Lu +3
Vision-language large models are moving toward the unification of visual understanding and visual generation tasks. However, whether generation can enhance understanding is still u…
Fine-grained Multiple Supervisory Network for Multi-modal Manipulation Detecting and Grounding
Xinquan Yu, Wei Lu, Xiangyang Luo
The task of Detecting and Grounding Multi-Modal Media Manipulation (DGM) is a branch of misinformation detection. Unlike traditional binary classification, it includes complex…
Weakly Supervised Multimodal Temporal Forgery Localization via Multitask Learning
Wenbo Xu, Wei Lu, Xiangyang Luo
The spread of Deepfake videos has caused a trust crisis and impaired social stability. Although numerous approaches have been proposed to address the challenges of Deepfake detecti…
A Multimodal Deviation Perceiving Framework for Weakly-Supervised Temporal Forgery Localization
Wenbo Xu, Junyan Wu, Wei Lu +2
Current researches on Deepfake forensics often treat detection as a classification task or temporal forgery localization problem, which are usually restrictive, time-consuming, and…
Weakly-Supervised Image Forgery Localization via Vision-Language Collaborative Reasoning Framework
Ziqi Sheng, Junyan Wu, Wei Lu +1
Image forgery localization aims to precisely identify tampered regions within images, but it commonly depends on costly pixel-level annotations. To alleviate this annotation burden…
StyleSentinel: Reliable Artistic Copyright Verification via Stylistic Fingerprints
Lingxiao Chen, Liqin Wang, Wei Lu
The versatility of diffusion models in generating customized images has led to unauthorized usage of personal artwork, which poses a significant threat to the intellectual property…
Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization
Qilin Yin, Wei Lu, Xiangyang Luo +1
Most research efforts in the multimedia forensics domain have focused on detecting forgery audio-visual content and reached sound achievements. However, these works only consider d…
ARIW-Framework: Adaptive Robust Iterative Watermarking Framework
Shaowu Wu, Liting Zeng, Wei Lu +1
With the rapid rise of large models, copyright protection for generated image content has become a critical security challenge. Although deep learning watermarking techniques offer…
Towards Open-world Generalized Deepfake Detection: General Feature Extraction via Unsupervised Domain Adaptation
Midou Guo, Qilin Yin, Wei Lu +1
With the development of generative artificial intelligence, new forgery methods are rapidly emerging. Social platforms are flooded with vast amounts of unlabeled synthetic data and…
Weakly-supervised Audio Temporal Forgery Localization via Progressive Audio-language Co-learning Network
Junyan Wu, Wenbo Xu, Wei Lu +3
Audio temporal forgery localization (ATFL) aims to find the precise forgery regions of the partial spoof audio that is purposefully modified. Existing ATFL methods rely on training…
Anti-Inpainting: A Proactive Defense Approach against Malicious Diffusion-based Inpainters under Unknown Conditions
Yimao Guo, Zuomin Qu, Wei Lu +1
With the increasing prevalence of diffusion-based malicious image manipulation, existing proactive defense methods struggle to safeguard images against tampering under unknown cond…
VoiceCloak: A Multi-Dimensional Defense Framework against Unauthorized Diffusion-based Voice Cloning
Qianyue Hu, Junyan Wu, Wei Lu +1
Diffusion Models (DMs) have achieved remarkable success in realistic voice cloning (VC), while they also increase the risk of malicious misuse. Existing proactive defenses designed…
Diffusion-based Adversarial Identity Manipulation for Facial Privacy Protection
Liqin Wang, Qianyue Hu, Wei Lu +1
The success of face recognition (FR) systems has led to serious privacy concerns due to potential unauthorized surveillance and user tracking on social networks. Existing methods f…
FakeScope: Large Multimodal Expert Model for Transparent AI-Generated Image Forensics
Yixuan Li, Yu Tian, Yipo Huang +4
The rapid and unrestrained advancement of generative artificial intelligence (AI) presents a double-edged sword. While enabling unprecedented creativity, it also facilitates the ge…
SUMI-IFL: An Information-Theoretic Framework for Image Forgery Localization with Sufficiency and Minimality Constraints
Ziqi Sheng, Wei Lu, Xiangyang Luo +2
Image forgery localization (IFL) is a crucial technique for preventing tampered image misuse and protecting social safety. However, due to the rapid development of image tampering…