41 citations · 94 across the 12 of their papers we have counts for
13 papers
Lazy Layers to Make Fine-Tuned Diffusion Models More Traceable
Haozhe Liu, Wentian Zhang, Bing Li +2
Foundational generative models should be traceable to protect their owners and facilitate safety regulation. To achieve this, traditional approaches embed identifiers based on supe…
Faster Diffusion via Temporal Attention Decomposition
Haozhe Liu, Wentian Zhang, Jinheng Xie +6
We explore the role of attention mechanism during inference in text-conditional diffusion models. Empirical observations suggest that cross-attention outputs converge to a fixed po…
Fingerprint Presentation Attack Detector Using Global-Local Model
Haozhe Liu, Wentian Zhang, Feng Liu +2
The vulnerability of automated fingerprint recognition systems (AFRSs) to presentation attacks (PAs) promotes the vigorous development of PA detection (PAD) technology. However, PA…
Dual Teacher Knowledge Distillation with Domain Alignment for Face Anti-spoofing
Zhe Kong, Wentian Zhang, Tao Wang +4
Face recognition systems have raised concerns due to their vulnerability to different presentation attacks, and system security has become an increasingly critical concern. Althoug…
BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion
Jinheng Xie, Yuexiang Li, Yawen Huang +4
Recent text-to-image diffusion models have demonstrated an astonishing capacity to generate high-quality images. However, researchers mainly studied the way of synthesizing images…
Dynamically Masked Discriminator for Generative Adversarial Networks
Wentian Zhang, Haozhe Liu, Bing Li +5
Training Generative Adversarial Networks (GANs) remains a challenging problem. The discriminator trains the generator by learning the distribution of real/generated data. However,…
Improving GAN Training via Feature Space Shrinkage
Haozhe Liu, Wentian Zhang, Bing Li +6
Due to the outstanding capability for data generation, Generative Adversarial Networks (GANs) have attracted considerable attention in unsupervised learning. However, training GANs…
Decoupled Mixup for Generalized Visual Recognition
Haozhe Liu, Wentian Zhang, Jinheng Xie +7
Convolutional neural networks (CNN) have demonstrated remarkable performance when the training and testing data are from the same distribution. However, such trained CNN models oft…
A Uniform Representation Learning Method for OCT-based Fingerprint Presentation Attack Detection and Reconstruction
Wentian Zhang, Haozhe Liu, Feng Liu +1
The technology of optical coherence tomography (OCT) to fingerprint imaging opens up a new research potential for fingerprint recognition owing to its ability to capture depth info…
FRT-PAD: Effective Presentation Attack Detection Driven by Face Related Task
Wentian Zhang, Haozhe Liu, Feng Liu +2
The robustness and generalization ability of Presentation Attack Detection (PAD) methods is critical to ensure the security of Face Recognition Systems (FRSs). However, in a real s…
Fingerprint Presentation Attack Detection by Channel-wise Feature Denoising
Feng Liu, Zhe Kong, Haozhe Liu +2
Due to the diversity of attack materials, fingerprint recognition systems (AFRSs) are vulnerable to malicious attacks. It is thus important to propose effective fingerprint present…
Taming Self-Supervised Learning for Presentation Attack Detection: De-Folding and De-Mixing
Zhe Kong, Wentian Zhang, Feng Liu +4
Biometric systems are vulnerable to Presentation Attacks (PA) performed using various Presentation Attack Instruments (PAIs). Even though there are numerous Presentation Attack Det…
A Zero-Shot based Fingerprint Presentation Attack Detection System
Haozhe Liu, Wentian Zhang, Guojie Liu +1
With the development of presentation attacks, Automated Fingerprint Recognition Systems(AFRSs) are vulnerable to presentation attack. Thus, numerous methods of presentation attack…