Search Results for author: Simon S. Woo

Found 21 papers, 10 papers with code

OTJR: Optimal Transport Meets Optimal Jacobian Regularization for Adversarial Robustness

no code implementations21 Mar 2023 Binh M. Le, Shahroz Tariq, Simon S. Woo

First, our work carefully analyzes and characterizes these two schools of approaches, both theoretically and empirically, to demonstrate how each approach impacts the robust learning of a classifier.

Adversarial Attack Adversarial Robustness

Interpretations Cannot Be Trusted: Stealthy and Effective Adversarial Perturbations against Interpretable Deep Learning

no code implementations29 Nov 2022 Eldor Abdukhamidov, Mohammed Abuhamad, Simon S. Woo, Eric Chan-Tin, Tamer Abuhmed

We assess the effectiveness of proposed attacks against two deep learning model architectures coupled with four interpretation models that represent different categories of interpretation models.

CFL-Net: Image Forgery Localization Using Contrastive Learning

no code implementations4 Oct 2022 Fahim Faisal Niloy, Kishor Kumar Bhaumik, Simon S. Woo

A key assumption in underlying forged region localization is that there remains a difference of feature distribution between untampered and manipulated regions in each forged image sample, irrespective of the forgery type.

Contrastive Learning Image Manipulation

Towards an Awareness of Time Series Anomaly Detection Models' Adversarial Vulnerability

1 code implementation24 Aug 2022 Shahroz Tariq, Binh M. Le, Simon S. Woo

To the best of our understanding, we demonstrate, for the first time, the vulnerabilities of anomaly detection systems against adversarial attacks.

Anomaly Detection Time Series Anomaly Detection

Deepfake Detection for Facial Images with Facemasks

no code implementations23 Feb 2022 Donggeun Ko, Sangjun Lee, Jinyong Park, Saebyeol Shin, Donghee Hong, Simon S. Woo

However, none of the suggested deepfakedetection methods assessed the performance of deepfakes withthe facemask during the pandemic crisis after the outbreak of theCovid-19.

DeepFake Detection Face Swapping +1

KappaFace: Adaptive Additive Angular Margin Loss for Deep Face Recognition

no code implementations19 Jan 2022 Chingis Oinar, Binh M. Le, Simon S. Woo

However, the majority of the proposed methods do not consider the class imbalance issue, which is a major challenge in practice for developing deep face recognition models.

Face Recognition

DA-FDFtNet: Dual Attention Fake Detection Fine-tuning Network to Detect Various AI-Generated Fake Images

no code implementations22 Dec 2021 Young Oh Bang, Simon S. Woo

Our DA-FDFtNet integrates the pre-trained model with Fine-Tune Transformer, MBblockV3, and a channel attention module to improve the performance and robustness across different types of fake images.

Few-Shot Learning

Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images

1 code implementation15 Dec 2021 Binh M. Le, Simon S. Woo

The rapid progression of Generative Adversarial Networks (GANs) has raised a concern of their misuse for malicious purposes, especially in creating fake face images.

ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images

no code implementations7 Dec 2021 Binh M. Le, Simon S. Woo

In particular, we propose the Attention-based Deepfake detection Distiller (ADD), which consists of two novel distillations: 1) frequency attention distillation that effectively retrieves the removed high-frequency components in the student network, and 2) multi-view attention distillation that creates multiple attention vectors by slicing the teacher's and student's tensors under different views to transfer the teacher tensor's distribution to the student more efficiently.

DeepFake Detection Face Swapping +2

Evaluating the Robustness of Time Series Anomaly and Intrusion Detection Methods against Adversarial Attacks

no code implementations29 Sep 2021 Shahroz Tariq, Simon S. Woo

To the best of our knowledge, we are the first to demonstrate the vulnerabilities of anomaly and intrusion detection systems against adversarial attacks.

Intrusion Detection Time Series Analysis

Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors

no code implementations7 Sep 2021 Hasam Khalid, Minha Kim, Shahroz Tariq, Simon S. Woo

On the other hand, to develop a good deepfake detector that can cope with the recent advancements in deepfake generation, we need to have a detector that can detect deepfakes of multiple modalities, i. e., videos and audios.

DeepFake Detection Face Swapping

CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation

2 code implementations6 Jul 2021 Minha Kim, Shahroz Tariq, Simon S. Woo

Over the last few decades, artificial intelligence research has made tremendous strides, but it still heavily relies on fixed datasets in stationary environments.

Continual Learning Domain Adaptation +3

One Detector to Rule Them All: Towards a General Deepfake Attack Detection Framework

1 code implementation1 May 2021 Shahroz Tariq, Sangyup Lee, Simon S. Woo

Beyond detecting a single type of DF from benchmark deepfake datasets, we focus on developing a generalized approach to detect multiple types of DFs, including deepfakes from unknown generation methods such as DeepFake-in-the-Wild (DFW) videos.

Face Swapping

Am I a Real or Fake Celebrity? Measuring Commercial Face Recognition Web APIs under Deepfake Impersonation Attack

no code implementations1 Mar 2021 Shahroz Tariq, Sowon Jeon, Simon S. Woo

Moreover, we propose practical defense strategies to mitigate DI attacks, reducing the attack success rates to as low as 0% and 0. 02% for targeted and non-targeted attacks, respectively.

Face Recognition Face Swapping

T-GD: Transferable GAN-generated Images Detection Framework

1 code implementation ICML 2020 Hyeonseong Jeon, Youngoh Bang, Junyaup Kim, Simon S. Woo

First, we train the teacher model on the source dataset and use it as a starting point for learning the target dataset.

FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning Network

2 code implementations5 Jan 2020 Hyeonseong Jeon, Youngoh Bang, Simon S. Woo

Creating fake images and videos such as "Deepfake" has become much easier these days due to the advancement in Generative Adversarial Networks (GANs).

Face Swapping Few-Shot Learning +2

Cannot find the paper you are looking for? You can Submit a new open access paper.