48 citations · 60 across the 30 of their papers we have counts for
30 papers
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…
iFADIT: Invertible Face Anonymization via Disentangled Identity Transform
Lin Yuan, Kai Liang, Xiong Li +3
Face anonymization aims to conceal the visual identity of a face to safeguard the individual's privacy. Traditional methods like blurring and pixelation can largely remove identify…
Motion Artifact Removal in Pixel-Frequency Domain via Alternate Masks and Diffusion Model
Jiahua Xu, Dawei Zhou, Lei Hu +5
Motion artifacts present in magnetic resonance imaging (MRI) can seriously interfere with clinical diagnosis. Removing motion artifacts is a straightforward solution and has been e…
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…
InstructBrush: Learning Attention-based Instruction Optimization for Image Editing
Ruoyu Zhao, Qingnan Fan, Fei Kou +7
In recent years, instruction-based image editing methods have garnered significant attention in image editing. However, despite encompassing a wide range of editing priors, these m…
Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structure
De Cheng, Yanling Ji, Dong Gong +4
In real-world applications, image degeneration caused by adverse weather is always complex and changes with different weather conditions from days and seasons. Systems in real-worl…
Exploring Homogeneous and Heterogeneous Consistent Label Associations for Unsupervised Visible-Infrared Person ReID
Lingfeng He, De Cheng, Nannan Wang +1
Unsupervised visible-infrared person re-identification (USL-VI-ReID) endeavors to retrieve pedestrian images of the same identity from different modalities without annotations. Whi…
Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors
Shiyin Dong, Mingrui Zhu, Kun Cheng +2
The remarkable prowess of diffusion models in image generation has spurred efforts to extend their application beyond generative tasks. However, a persistent challenge exists in la…
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…
Point Deformable Network with Enhanced Normal Embedding for Point Cloud Analysis
Xingyilang Yin, Xi Yang, Liangchen Liu +2
Recently MLP-based methods have shown strong performance in point cloud analysis. Simple MLP architectures are able to learn geometric features in local point groups yet fail to mo…
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…
Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking
Yan Gao, Haojun Xu, Nannan Wang +2
The global multi-object tracking (MOT) system can consider interaction, occlusion, and other ``visual blur'' scenarios to ensure effective object tracking in long videos. Among the…
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…
EtC: Temporal Boundary Expand then Clarify for Weakly Supervised Video Grounding with Multimodal Large Language Model
Guozhang Li, Xinpeng Ding, De Cheng +3
Early weakly supervised video grounding (WSVG) methods often struggle with incomplete boundary detection due to the absence of temporal boundary annotations. To bridge the gap betw…
CatVersion: Concatenating Embeddings for Diffusion-Based Text-to-Image Personalization
Ruoyu Zhao, Mingrui Zhu, Shiyin Dong +2
We propose CatVersion, an inversion-based method that learns the personalized concept through a handful of examples. Subsequently, users can utilize text prompts to generate images…
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…
Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria
Nuoyan Zhou, Nannan Wang, Decheng Liu +2
Deep neural networks are vulnerable to adversarial noise. Adversarial Training (AT) has been demonstrated to be the most effective defense strategy to protect neural networks from…
Disentangle Before Anonymize: A Two-stage Framework for Attribute-preserved and Occlusion-robust De-identification
Mingrui Zhu, Dongxin Chen, Xin Wei +2
In an era where personal photos are easily leaked and collected, face de-identification is a crucial method for protecting identity privacy. However, current face de-identification…
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…
PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow
Lin Yuan, Kai Liang, Xiao Pu +5
This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single…