82 citations · 234 across the 22 of their papers we have counts for
22 papers
The NeRF Signature: Codebook-Aided Watermarking for Neural Radiance Fields
Ziyuan Luo, Anderson Rocha, Boxin Shi +3
Neural Radiance Fields (NeRF) have been gaining attention as a significant form of 3D content representation. With the proliferation of NeRF-based creations, the need for copyright…
Image Provenance Analysis via Graph Encoding with Vision Transformer
Keyang Zhang, Chenqi Kong, Shiqi Wang +2
Recent advances in AI-powered image editing tools have significantly lowered the barrier to image modification, raising pressing security concerns those related to spreading misinf…
Universal and Extensible Language-Vision Models for Organ Segmentation and Tumor Detection from Abdominal Computed Tomography
Jie Liu, Yixiao Zhang, Kang Wang +8
The advancement of artificial intelligence (AI) for organ segmentation and tumor detection is propelled by the growing availability of computed tomography (CT) datasets with detail…
Gradient-Congruity Guided Federated Sparse Training
Chris Xing Tian, Yibing Liu, Haoliang Li +2
Edge computing allows artificial intelligence and machine learning models to be deployed on edge devices, where they can learn from local data and collaborate to form a global mode…
Robust Domain Misinformation Detection via Multi-modal Feature Alignment
Hui Liu, Wenya Wang, Hao Sun +2
Social media misinformation harms individuals and societies and is potentialized by fast-growing multi-modal content (i.e., texts and images), which accounts for higher "credibilit…
Pixel-Inconsistency Modeling for Image Manipulation Localization
Chenqi Kong, Anwei Luo, Shiqi Wang +3
Digital image forensics plays a crucial role in image authentication and manipulation localization. Despite the progress powered by deep neural networks, existing forgery localizat…
The Age of Synthetic Realities: Challenges and Opportunities
João Phillipe Cardenuto, Jing Yang, Rafael Padilha +7
Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of…
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
Yibing Liu, Chris Xing Tian, Haoliang Li +2
The out-of-distribution (OOD) problem generally arises when neural networks encounter data that significantly deviates from the training data distribution, i.e., in-distribution (I…
Enhancing General Face Forgery Detection via Vision Transformer with Low-Rank Adaptation
Chenqi Kong, Haoliang Li, Shiqi Wang
Nowadays, forgery faces pose pressing security concerns over fake news, fraud, impersonation, etc. Despite the demonstrated success in intra-domain face forgery detection, existing…
M3FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing System
Chenqi Kong, Kexin Zheng, Yibing Liu +3
Face presentation attacks (FPA), also known as face spoofing, have brought increasing concerns to the public through various malicious applications, such as financial fraud and pri…
Generalization Beyond Feature Alignment: Concept Activation-Guided Contrastive Learning
Yibing Liu, Chris Xing Tian, Haoliang Li +1
Learning invariant representations via contrastive learning has seen state-of-the-art performance in domain generalization (DG). Despite such success, in this paper, we find that i…
Digital and Physical Face Attacks: Reviewing and One Step Further
Chenqi Kong, Shiqi Wang, Haoliang Li
With the rapid progress over the past five years, face authentication has become the most pervasive biometric recognition method. Thanks to the high-accuracy recognition performanc…
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…
Rethinking Attention-Model Explainability through Faithfulness Violation Test
Yibing Liu, Haoliang Li, Yangyang Guo +3
Attention mechanisms are dominating the explainability of deep models. They produce probability distributions over the input, which are widely deemed as feature-importance indicato…
Asymmetric Modality Translation For Face Presentation Attack Detection
Zhi Li, Haoliang Li, Xin Luo +3
Face presentation attack detection (PAD) is an essential measure to protect face recognition systems from being spoofed by malicious users and has attracted great attention from bo…
Detect and Locate: Exposing Face Manipulation by Semantic- and Noise-level Telltales
Chenqi Kong, Baoliang Chen, Haoliang Li +3
The technological advancements of deep learning have enabled sophisticated face manipulation schemes, raising severe trust issues and security concerns in modern society. Generally…
Privacy-Preserving Constrained Domain Generalization via Gradient Alignment
Chris Xing Tian, Haoliang Li, Yufei Wang +1
Deep neural networks (DNN) have demonstrated unprecedented success for medical imaging applications. However, due to the issue of limited dataset availability and the strict legal…
Neuron Coverage-Guided Domain Generalization
Chris Xing Tian, Haoliang Li, Xiaofei Xie +2
This paper focuses on the domain generalization task where domain knowledge is unavailable, and even worse, only samples from a single domain can be utilized during training. Our m…
Camera Invariant Feature Learning for Generalized Face Anti-spoofing
Baoliang Chen, Wenhan Yang, Haoliang Li +2
There has been an increasing consensus in learning based face anti-spoofing that the divergence in terms of camera models is causing a large domain gap in real application scenario…
Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization
Haoliang Li, YuFei Wang, Renjie Wan +3
Recently, we have witnessed great progress in the field of medical imaging classification by adopting deep neural networks. However, the recent advanced models still require access…
Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems
Haoliang Li, Yufei Wang, Xiaofei Xie +5
Deep neural networks (DNN) have shown great success in many computer vision applications. However, they are also known to be susceptible to backdoor attacks. When conducting backdo…
No-reference Screen Content Image Quality Assessment with Unsupervised Domain Adaptation
Baoliang Chen, Haoliang Li, Hongfei Fan +1
In this paper, we quest the capability of transferring the quality of natural scene images to the images that are not acquired by optical cameras (e.g., screen content images, SCIs…