activity
20182025
most citedUse of a Capsule Network to Detect Fake Images and Videos

132 citations · 285 across the 36 of their papers we have counts for

collaborators

36 papers

cs.CV2025

Exploring Active Data Selection Strategies for Continuous Training in Deepfake Detection

Yoshihiko Furuhashi, Junichi Yamagishi, Xin Wang +2

In deepfake detection, it is essential to maintain high performance by adjusting the parameters of the detector as new deepfake methods emerge. In this paper, we propose a method t…

cs.CV2024

Physics-Based Adversarial Attack on Near-Infrared Human Detector for Nighttime Surveillance Camera Systems

Muyao Niu, Zhuoxiao Li, Yifan Zhan +3

Many surveillance cameras switch between daytime and nighttime modes based on illuminance levels. During the day, the camera records ordinary RGB images through an enabled IR-cut f…

cs.CV2024★ 2 cited

Variational Autoencoder for Anomaly Detection: A Comparative Study

Huy Hoang Nguyen, Cuong Nhat Nguyen, Xuan Tung Dao +3

This paper aims to conduct a comparative analysis of contemporary Variational Autoencoder (VAE) architectures employed in anomaly detection, elucidating their performance and behav…

cs.CV2024

LookupForensics: A Large-Scale Multi-Task Dataset for Multi-Phase Image-Based Fact Verification

Shuhan Cui, Huy H. Nguyen, Trung-Nghia Le +2

Amid the proliferation of forged images, notably the tsunami of deepfake content, extensive research has been conducted on using artificial intelligence (AI) to identify forged con…

cs.CV2024

Mitigating Backdoor Attacks using Activation-Guided Model Editing

Felix Hsieh, Huy H. Nguyen, AprilPyone MaungMaung +2

Backdoor attacks compromise the integrity and reliability of machine learning models by embedding a hidden trigger during the training process, which can later be activated to caus…

cs.CV2024★ 1 cited

Exploring Self-Supervised Vision Transformers for Deepfake Detection: A Comparative Analysis

Huy H. Nguyen, Junichi Yamagishi, Isao Echizen

This paper investigates the effectiveness of self-supervised pre-trained vision transformers (ViTs) compared to supervised pre-trained ViTs and conventional neural networks (ConvNe…

cs.CV2024★ 3 cited

Image-Text Out-Of-Context Detection Using Synthetic Multimodal Misinformation

Fatma Shalabi, Huy H. Nguyen, Hichem Felouat +2

Misinformation has become a major challenge in the era of increasing digital information, requiring the development of effective detection methods. We have investigated a novel app…

cs.CV2024

Leveraging Chat-Based Large Vision Language Models for Multimodal Out-Of-Context Detection

Fatma Shalabi, Hichem Felouat, Huy H. Nguyen +1

Out-of-context (OOC) detection is a challenging task involving identifying images and texts that are irrelevant to the context in which they are presented. Large vision-language mo…

cs.CV2024

Fine-Tuning Text-To-Image Diffusion Models for Class-Wise Spurious Feature Generation

AprilPyone MaungMaung, Huy H. Nguyen, Hitoshi Kiya +1

We propose a method for generating spurious features by leveraging large-scale text-to-image diffusion models. Although the previous work detects spurious features in a large-scale…

cs.CL2024

Enhancing Robustness of LLM-Synthetic Text Detectors for Academic Writing: A Comprehensive Analysis

Zhicheng Dou, Yuchen Guo, Ching-Chun Chang +2

The emergence of large language models (LLMs), such as Generative Pre-trained Transformer 4 (GPT-4) used by ChatGPT, has profoundly impacted the academic and broader community. Whi…

cs.CL2024★ 4 cited

Cross-Attention Watermarking of Large Language Models

Folco Bertini Baldassini, Huy H. Nguyen, Ching-Chung Chang +1

A new approach to linguistic watermarking of language models is presented in which information is imperceptibly inserted into the output text while preserving its readability and o…

cs.CV2024

Surface Normal Estimation with Transformers

Barry Shichen Hu, Siyun Liang, Johannes Paetzold +3

We propose the use of a Transformer to accurately predict normals from point clouds with noise and density variations. Previous learning-based methods utilize PointNet variants to…

cs.CV2023★ 1 cited

Generalized Deepfakes Detection with Reconstructed-Blended Images and Multi-scale Feature Reconstruction Network

Yuyang Sun, Huy H. Nguyen, Chun-Shien Lu +3

The growing diversity of digital face manipulation techniques has led to an urgent need for a universal and robust detection technology to mitigate the risks posed by malicious for…

cs.SE2023★ 1 cited

Quality Assurance of A GPT-based Sentiment Analysis System: Adversarial Review Data Generation and Detection

Tinghui Ouyang, Hoang-Quoc Nguyen-Son, Huy H. Nguyen +2

Large Language Models (LLMs) have been garnering significant attention of AI researchers, especially following the widespread popularity of ChatGPT. However, due to LLMs' intricate…

cs.CV2023

How Close are Other Computer Vision Tasks to Deepfake Detection?

Huy H. Nguyen, Junichi Yamagishi, Isao Echizen

In this paper, we challenge the conventional belief that supervised ImageNet-trained models have strong generalizability and are suitable for use as feature extractors in deepfake…

cs.CV2023★ 1 cited

Defending Against Physical Adversarial Patch Attacks on Infrared Human Detection

Lukas Strack, Futa Waseda, Huy H. Nguyen +2

Infrared detection is an emerging technique for safety-critical tasks owing to its remarkable anti-interference capability. However, recent studies have revealed that it is vulnera…

cs.CR2023★ 16 cited

Cyber Vaccine for Deepfake Immunity

Ching-Chun Chang, Huy Hong Nguyen, Junichi Yamagishi +1

Deepfakes pose an evolving threat to cybersecurity, which calls for the development of automated countermeasures. While considerable forensic research has been devoted to the detec…

cs.CV2022★ 2 cited

Face Forgery Detection Based on Facial Region Displacement Trajectory Series

YuYang Sun, ZhiYong Zhang, Isao Echizen +3

Deep-learning-based technologies such as deepfakes ones have been attracting widespread attention in both society and academia, particularly ones used to synthesize forged face ima…

cs.CV2022

Analysis of Master Vein Attacks on Finger Vein Recognition Systems

Huy H. Nguyen, Trung-Nghia Le, Junichi Yamagishi +1

Finger vein recognition (FVR) systems have been commercially used, especially in ATMs, for customer verification. Thus, it is essential to measure their robustness against various…

cs.CV2022

Rethinking Adversarial Examples for Location Privacy Protection

Trung-Nghia Le, Ta Gu, Huy H. Nguyen +1

We have investigated a new application of adversarial examples, namely location privacy protection against landmark recognition systems. We introduce mask-guided multimodal project…

cs.CV2022

Robust Deepfake On Unrestricted Media: Generation And Detection

Trung-Nghia Le, Huy H Nguyen, Junichi Yamagishi +1

Recent advances in deep learning have led to substantial improvements in deepfake generation, resulting in fake media with a more realistic appearance. Although deepfake media have…

cs.LG2021★ 5 cited

Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently

Futa Waseda, Sosuke Nishikawa, Trung-Nghia Le +2

Deep neural networks are vulnerable to adversarial examples (AEs), which have adversarial transferability: AEs generated for the source model can mislead another (target) model's p…

cs.CV2021

Master Face Attacks on Face Recognition Systems

Huy H. Nguyen, Sébastien Marcel, Junichi Yamagishi +1

Face authentication is now widely used, especially on mobile devices, rather than authentication using a personal identification number or an unlock pattern, due to its convenience…

cs.CV2021★ 1 cited

OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wild

Trung-Nghia Le, Huy H. Nguyen, Junichi Yamagishi +1

The proliferation of deepfake media is raising concerns among the public and relevant authorities. It has become essential to develop countermeasures against forged faces in social…