77 citations · 105 across the 22 of their papers we have counts for
24 papers
EviStress: Evidence Stress Learning for Generalizable Face Forgery Detection with Textual Explanations
Jiuyao Jing, Xuanyu Yi, Yu Zheng +1
The rapid spread of face forgeries on the Web challenges the credibility of visual content. In practical Web environments, manipulated media originate from evolving generation pipe…
Trio: Learning Time-Series Forecasting with Temporal-Spatial-Sample Attention and Structural Causal Priors
Tao Chen, Yexu Zhou, Zhi Gong +9
Multivariate time-series forecasting requires models to reason over temporal dynamics, cross-variable dependencies, and historical input-output correspondences. Recent Prior-Data F…
Bridging Data Trials and Task Barriers: A Unified Framework for Sketch Biometric Identification
Decheng Liu, Bin Hu, Xinbo Gao +4
Different from existing cross-modality identification tasks (e.g., heterogeneous face recognition, sketch re-identification, etc.), we introduce a novel yet practical setting for t…
MGFFD-VLM: Multi-Granularity Prompt Learning for Face Forgery Detection with VLM
Tao Chen, Jingyi Zhang, Decheng Liu +1
Recent studies have utilized visual large language models (VLMs) to answer not only "Is this face a forgery?" but also "Why is the face a forgery?" These studies introduced forgery…
Thinking Racial Bias in Fair Forgery Detection: Models, Datasets and Evaluations
Decheng Liu, Zongqi Wang, Chunlei Peng +3
Due to the successful development of deep image generation technology, forgery detection plays a more important role in social and economic security. Racial bias has not been explo…
Federated Face Forgery Detection Learning with Personalized Representation
Decheng Liu, Zhan Dang, Chunlei Peng +3
Deep generator technology can produce high-quality fake videos that are indistinguishable, posing a serious social threat. Traditional forgery detection methods directly centralize…
Improving Adversarial Robustness via Decoupled Visual Representation Masking
Decheng Liu, Tao Chen, Chunlei Peng +3
Deep neural networks are proven to be vulnerable to fine-designed adversarial examples, and adversarial defense algorithms draw more and more attention nowadays. Pre-processing bas…
Imperceptible Face Forgery Attack via Adversarial Semantic Mask
Decheng Liu, Qixuan Su, Chunlei Peng +2
With the great development of generative model techniques, face forgery detection draws more and more attention in the related field. Researchers find that existing face forgery mo…
Semi-Supervised Learning for Anomaly Traffic Detection via Bidirectional Normalizing Flows
Zhangxuan Dang, Yu Zheng, Xinglin Lin +3
With the rapid development of the Internet, various types of anomaly traffic are threatening network security. We consider the problem of anomaly network traffic detection and prop…
Masked Attribute Description Embedding for Cloth-Changing Person Re-identification
Chunlei Peng, Boyu Wang, Decheng Liu +3
Cloth-changing person re-identification (CC-ReID) aims to match persons who change clothes over long periods. The key challenge in CC-ReID is to extract clothing-independent featur…
Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion Model
Decheng Liu, Xijun Wang, Chunlei Peng +3
Adversarial attacks involve adding perturbations to the source image to cause misclassification by the target model, which demonstrates the potential of attacking face recognition…
Symmetrical Bidirectional Knowledge Alignment for Zero-Shot Sketch-Based Image Retrieval
Decheng Liu, Xu Luo, Chunlei Peng +3
This paper studies the problem of zero-shot sketch-based image retrieval (ZS-SBIR), which aims to use sketches from unseen categories as queries to match the images of the same cat…
DeepFidelity: Perceptual Forgery Fidelity Assessment for Deepfake Detection
Chunlei Peng, Huiqing Guo, Decheng Liu +3
Deepfake detection refers to detecting artificially generated or edited faces in images or videos, which plays an essential role in visual information security. Despite promising p…
GazeForensics: DeepFake Detection via Gaze-guided Spatial Inconsistency Learning
Qinlin He, Chunlei Peng, Decheng Liu +2
DeepFake detection is pivotal in personal privacy and public safety. With the iterative advancement of DeepFake techniques, high-quality forged videos and images are becoming incre…
Attention Consistency Refined Masked Frequency Forgery Representation for Generalizing Face Forgery Detection
Decheng Liu, Tao Chen, Chunlei Peng +3
Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security. Existing forg…
Hierarchical Forgery Classifier On Multi-modality Face Forgery Clues
Decheng Liu, Zeyang Zheng, Chunlei Peng +3
Face forgery detection plays an important role in personal privacy and social security. With the development of adversarial generative models, high-quality forgery images become mo…
Multi-view Multi-label Anomaly Network Traffic Classification based on MLP-Mixer Neural Network
Yu Zheng, Zhangxuan Dang, Chunlei Peng +2
Network traffic classification is the basis of many network security applications and has attracted enough attention in the field of cyberspace security. Existing network traffic c…
FedForgery: Generalized Face Forgery Detection with Residual Federated Learning
Decheng Liu, Zhan Dang, Chunlei Peng +4
With the continuous development of deep learning in the field of image generation models, a large number of vivid forged faces have been generated and spread on the Internet. These…
TransFA: Transformer-based Representation for Face Attribute Evaluation
Decheng Liu, Weijie He, Chunlei Peng +3
Face attribute evaluation plays an important role in video surveillance and face analysis. Although methods based on convolution neural networks have made great progress, they inev…
Spatial-Temporal Frequency Forgery Clue for Video Forgery Detection in VIS and NIR Scenario
Yukai Wang, Chunlei Peng, Decheng Liu +2
In recent years, with the rapid development of face editing and generation, more and more fake videos are circulating on social media, which has caused extreme public concerns. Exi…
Towards Defending against Adversarial Examples via Attack-Invariant Features
Dawei Zhou, Tongliang Liu, Bo Han +3
Deep neural networks (DNNs) are vulnerable to adversarial noise. Their adversarial robustness can be improved by exploiting adversarial examples. However, given the continuously ev…
Removing Adversarial Noise in Class Activation Feature Space
Dawei Zhou, Nannan Wang, Chunlei Peng +4
Deep neural networks (DNNs) are vulnerable to adversarial noise. Preprocessing based defenses could largely remove adversarial noise by processing inputs. However, they are typical…
Sparse Graphical Representation based Discriminant Analysis for Heterogeneous Face Recognition
Chunlei Peng, Xinbo Gao, Nannan Wang +1
Face images captured in heterogeneous environments, e.g., sketches generated by the artists or composite-generation software, photos taken by common cameras and infrared images cap…
Graphical Representation for Heterogeneous Face Recognition
Chunlei Peng, Xinbo Gao, Nannan Wang +1
Heterogeneous face recognition (HFR) refers to matching face images acquired from different sources (i.e., different sensors or different wavelengths) for identification. HFR plays…