1 citations · 3 across the 17 of their papers we have counts for
18 papers
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…
Rethinking Cross-Domain Evaluation for Face Forgery Detection with Semantic Fine-grained Alignment and Mixture-of-Experts
Yuhan Luo, Tao Chen, Decheng Liu
Nowadays, visual data forgery detection plays an increasingly important role in social and economic security with the rapid development of generative models. Existing face forgery…
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…
A Knowledge-guided Adversarial Defense for Resisting Malicious Visual Manipulation
Dawei Zhou, Suzhi Gang, Decheng Liu +3
Malicious applications of visual manipulation have raised serious threats to the security and reputation of users in many fields. To alleviate these issues, adversarial noise-based…
Towards Generalized Proactive Defense against Face Swapping with Contour-Hybrid Watermark
Ruiyang Xia, Dawei Zhou, Decheng Liu +4
Face swapping, recognized as a privacy and security concern, has prompted considerable defensive research. With the advancements in AI-generated content, the discrepancies between…
Improving Adversarial Robustness via Phase and Amplitude-aware Prompting
Yibo Xu, Dawei Zhou, Decheng Liu +1
Deep neural networks are found to be vulnerable to adversarial perturbations. The prompt-based defense has been increasingly studied due to its high efficiency. However, existing p…
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…
AFD: Mitigating Feature Gap for Adversarial Robustness by Feature Disentanglement
Nuoyan Zhou, Dawei Zhou, Decheng Liu +2
Adversarial fine-tuning methods enhance adversarial robustness via fine-tuning the pre-trained model in an adversarial training manner. However, we identify that some specific late…
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…
Toward Trustworthy Identity Tracing via Multi-attribute Synergistic Identification
Decheng Liu, Jiahao Yu, Ruimin Hu +1
Identity tracing is a technology that uses the selection and collection of identity attributes of the object to be tested to discover its true identity, and it is one of the most i…