270 citations · 962 across the 54 of their papers we have counts for
54 papers
Hyperbolic Face Anti-Spoofing
Shuangpeng Han, Rizhao Cai, Yawen Cui +3
Learning generalized face anti-spoofing (FAS) models against presentation attacks is essential for the security of face recognition systems. Previous FAS methods usually encourage…
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
Xin Liu, Kaishen Yuan, Xuesong Niu +4
Facial Action Unit (AU) detection is a crucial task in affective computing and social robotics as it helps to identify emotions expressed through facial expressions. Anatomically,…
Visual Prompt Flexible-Modal Face Anti-Spoofing
Zitong Yu, Rizhao Cai, Yawen Cui +2
Recently, vision transformer based multimodal learning methods have been proposed to improve the robustness of face anti-spoofing (FAS) systems. However, multimodal face data colle…
Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization
Yingxin Lai, Zhiming Luo, Zitong Yu
The rapid advancements in computer vision have stimulated remarkable progress in face forgery techniques, capturing the dedicated attention of researchers committed to detecting fo…
rPPG-MAE: Self-supervised Pre-training with Masked Autoencoders for Remote Physiological Measurement
Xin Liu, Yuting Zhang, Zitong Yu +3
Remote photoplethysmography (rPPG) is an important technique for perceiving human vital signs, which has received extensive attention. For a long time, researchers have focused on…
FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofing
Ajian Liu, Zichang Tan, Zitong Yu +7
The availability of handy multi-modal (i.e., RGB-D) sensors has brought about a surge of face anti-spoofing research. However, the current multi-modal face presentation attack dete…
Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less
Rizhao Cai, Yawen Cui, Zhi Li +4
Face Anti-Spoofing (FAS) is recently studied under the continual learning setting, where the FAS models are expected to evolve after encountering the data from new domains. However…
Neuron Structure Modeling for Generalizable Remote Physiological Measurement
Hao Lu, Zitong Yu, Xuesong Niu +1
Remote photoplethysmography (rPPG) technology has drawn increasing attention in recent years. It can extract Blood Volume Pulse (BVP) from facial videos, making many applications l…
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning
Xiaobao Guo, Nithish Muthuchamy Selvaraj, Zitong Yu +3
Deception detection in conversations is a challenging yet important task, having pivotal applications in many fields such as credibility assessment in business, multimedia anti-fra…
A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT
Md Ashequr Rahman, Zitong Yu, Barry A. Siegel +1
Deep-learning (DL)-based methods have shown significant promise in denoising myocardial perfusion SPECT images acquired at low dose. For clinical application of these methods, eval…
Generalized Few-Shot Continual Learning with Contrastive Mixture of Adapters
Yawen Cui, Zitong Yu, Rizhao Cai +3
The goal of Few-Shot Continual Learning (FSCL) is to incrementally learn novel tasks with limited labeled samples and preserve previous capabilities simultaneously, while current F…
Rethinking Vision Transformer and Masked Autoencoder in Multimodal Face Anti-Spoofing
Zitong Yu, Rizhao Cai, Yawen Cui +3
Recently, vision transformer (ViT) based multimodal learning methods have been proposed to improve the robustness of face anti-spoofing (FAS) systems. However, there are still no w…
Flexible-modal Deception Detection with Audio-Visual Adapter
Zhaoxu Li, Zitong Yu, Nithish Muthuchamy Selvaraj +4
Detecting deception by human behaviors is vital in many fields such as custom security and multimedia anti-fraud. Recently, audio-visual deception detection attracts more attention…
PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer
Zitong Yu, Yuming Shen, Jingang Shi +5
Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applicatio…
Face Presentation Attack Detection
Zitong Yu, Chenxu Zhao, Zhen Lei
Face recognition technology has been widely used in daily interactive applications such as checking-in and mobile payment due to its convenience and high accuracy. However, its vul…
Learning Motion-Robust Remote Photoplethysmography through Arbitrary Resolution Videos
Jianwei Li, Zitong Yu, Jingang Shi
Remote photoplethysmography (rPPG) enables non-contact heart rate (HR) estimation from facial videos which gives significant convenience compared with traditional contact-based mea…
Boosting Binary Neural Networks via Dynamic Thresholds Learning
Jiehua Zhang, Xueyang Zhang, Zhuo Su +5
Developing lightweight Deep Convolutional Neural Networks (DCNNs) and Vision Transformers (ViTs) has become one of the focuses in vision research since the low computational cost i…
Forensicability Assessment of Questioned Images in Recapturing Detection
Changsheng Chen, Lin Zhao, Rizhao Cai +3
Recapture detection of face and document images is an important forensic task. With deep learning, the performances of face anti-spoofing (FAS) and recaptured document detection ha…
Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cues
Zitong Yu, Rizhao Cai, Zhi Li +3
Face anti-spoofing (FAS) and face forgery detection play vital roles in securing face biometric systems from presentation attacks (PAs) and vicious digital manipulation (e.g., deep…
Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry
Yawen Cui, Zitong Yu, Wei Peng +1
Few-Shot Class-Incremental Learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples by avoiding the overfitting and catastrophic forgetting simultan…
Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofing
Zhuo Wang, Zezheng Wang, Zitong Yu +4
With diverse presentation attacks emerging continually, generalizable face anti-spoofing (FAS) has drawn growing attention. Most existing methods implement domain generalization (D…
ViTransPAD: Video Transformer using convolution and self-attention for Face Presentation Attack Detection
Zuheng Ming, Zitong Yu, Musab Al-Ghadi +3
Face Presentation Attack Detection (PAD) is an important measure to prevent spoof attacks for face biometric systems. Many works based on Convolution Neural Networks (CNNs) for fac…
Ideal-observer computation with anthropomorphic phantoms using Markov Chain Monte Carlo
Md Ashequr Rahman, Zitong Yu, Abhinav K. Jha
In medical imaging, it is widely recognized that image quality should be objectively evaluated based on performance in clinical tasks. To evaluate performance in signal-detection t…
Investigating the limited performance of a deep-learning-based SPECT denoising approach: An observer-study-based characterization
Zitong Yu, Md Ashequr Rahman, Abhinav K. Jha
Multiple objective assessment of image-quality-based studies have reported that several deep-learning-based denoising methods show limited performance on signal-detection tasks. Ou…