98 citations · 235 across the 21 of their papers we have counts for
21 papers
AI-driven Remote Facial Skin Hydration and TEWL Assessment from Selfie Images: A Systematic Solution
Cecelia Soh, Rizhao Cai, Monalisha Paul +2
Skin health and disease resistance are closely linked to the skin barrier function, which protects against environmental factors and water loss. Two key physiological indicators ca…
Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data Synthesis
Rizhao Cai, Cecelia Soh, Zitong Yu +3
Face Anti-Spoofing (FAS) research is challenged by the cross-domain problem, where there is a domain gap between the training and testing data. While recent FAS works are mainly mo…
Controllable and Gradual Facial Blemishes Retouching via Physics-Based Modelling
Chenhao Shuai, Rizhao Cai, Bandara Dissanayake +5
Face retouching aims to remove facial blemishes, such as pigmentation and acne, and still retain fine-grain texture details. Nevertheless, existing methods just remove the blemishe…
Suppress and Rebalance: Towards Generalized Multi-Modal Face Anti-Spoofing
Xun Lin, Shuai Wang, Rizhao Cai +5
Face Anti-Spoofing (FAS) is crucial for securing face recognition systems against presentation attacks. With advancements in sensor manufacture and multi-modal learning techniques,…
BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models
Rizhao Cai, Zirui Song, Dayan Guan +4
Large Multimodal Models (LMMs) such as GPT-4V and LLaVA have shown remarkable capabilities in visual reasoning with common image styles. However, their robustness against diverse s…
Generalized Face Forgery Detection via Adaptive Learning for Pre-trained Vision Transformer
Anwei Luo, Rizhao Cai, Chenqi Kong +4
With the rapid progress of generative models, the current challenge in face forgery detection is how to effectively detect realistic manipulated faces from different unseen domains…
S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens
Rizhao Cai, Zitong Yu, Chenqi Kong +4
Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a face recognition system by presenting spoofed faces. State-of-the-art FAS techniques predominantly rely on de…
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…
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…
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…
Evaluating the Efficacy of Skincare Product: A Realistic Short-Term Facial Pore Simulation
Ling Li, Bandara Dissanayake, Tatsuya Omotezako +8
Simulating the effects of skincare products on face is a potential new way to communicate the efficacy of skincare products in skin diagnostics and product recommendations. Further…
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…
Toward domain generalized pruning by scoring out-of-distribution importance
Rizhao Cai, Haoliang Li, Alex Kot
Filter pruning has been widely used for compressing convolutional neural networks to reduce computation costs during the deployment stage. Recent studies have shown that filter pru…
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…
One-Class Knowledge Distillation for Face Presentation Attack Detection
Zhi Li, Rizhao Cai, Haoliang Li +3
Face presentation attack detection (PAD) has been extensively studied by research communities to enhance the security of face recognition systems. Although existing methods have ac…
Automatic Facial Skin Feature Detection for Everyone
Qian Zheng, Ankur Purwar, Heng Zhao +11
Automatic assessment and understanding of facial skin condition have several applications, including the early detection of underlying health problems, lifestyle and dietary treatm…
Learning Meta Pattern for Face Anti-Spoofing
Rizhao Cai, Zhi Li, Renjie Wan +3
Face Anti-Spoofing (FAS) is essential to secure face recognition systems and has been extensively studied in recent years. Although deep neural networks (DNNs) for the FAS task hav…
DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing
Rizhao Cai, Haoliang Li, Shiqi Wang +2
Inspired by the philosophy employed by human beings to determine whether a presented face example is genuine or not, i.e., to glance at the example globally first and then carefull…
Learning deep forest with multi-scale Local Binary Pattern features for face anti-spoofing
Rizhao Cai, Changsheng Chen
Face Anti-Spoofing (FAS) is significant for the security of face recognition systems. Convolutional Neural Networks (CNNs) have been introduced to the field of the FAS and have ach…