4 citations · 13 across the 18 of their papers we have counts for
14 papers · 1 filter
FVeinSyn: Synthetic Finger Vein Image Generator
Yifan Wang, Jie Gui, Adams Wai Kin Kong +6
A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples per finger, restricting the ad…
IdentiFace: Multi-Modal Iterative Diffusion Framework for Identifiable Suspect Face Generation in Crime Investigations
Weichen Liu, Yixin Yang, Changsheng Chen +1
Suspect face generation remains a technical challenge in crime investigations. Traditional sketch-drawing workflows suffer from low efficiency and quality, while diffusion-based ap…
Learning Representation and Synergy Invariances: A Povable Framework for Generalized Multimodal Face Anti-Spoofing
Xun Lin, Shuai Wang, Yi Yu +6
Multimodal Face Anti-Spoofing (FAS) methods, which integrate multiple visual modalities, often suffer even more severe performance degradation than unimodal FAS when deployed in un…
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…
ForensicsSAM: Toward Robust and Unified Image Forgery Detection and Localization Resisting to Adversarial Attack
Rongxuan Peng, Shunquan Tan, Chenqi Kong +3
Parameter-efficient fine-tuning (PEFT) has emerged as a popular strategy for adapting large vision foundation models, such as the Segment Anything Model (SAM) and LLaVA, to downstr…
Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable Trigger
Yi Yu, Song Xia, Xun Lin +4
No-Reference Image Quality Assessment (NR-IQA), responsible for assessing the quality of a single input image without using any reference, plays a critical role in evaluating and o…
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…
Improving Concept Alignment in Vision-Language Concept Bottleneck Models
Nithish Muthuchamy Selvaraj, Xiaobao Guo, Adams Wai-Kin Kong +1
Concept Bottleneck Models (CBM) map images to human-interpretable concepts before making class predictions. Recent approaches automate CBM construction by prompting Large Language…
MoE-FFD: Mixture of Experts for Generalized and Parameter-Efficient Face Forgery Detection
Chenqi Kong, Anwei Luo, Peijun Bao +5
Deepfakes have recently raised significant trust issues and security concerns among the public. Compared to CNN face forgery detectors, ViT-based methods take advantage of the expr…
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,…
MIMIC: Mask Image Pre-training with Mix Contrastive Fine-tuning for Facial Expression Recognition
Fan Zhang, Xiaobao Guo, Xiaojiang Peng +1
Cutting-edge research in facial expression recognition (FER) currently favors the utilization of convolutional neural networks (CNNs) backbone which is supervisedly pre-trained on…
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…
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…