Search Results for author: Yuezun Li

Found 21 papers, 7 papers with code

DomainForensics: Exposing Face Forgery across Domains via Bi-directional Adaptation

no code implementations17 Dec 2023 Qingxuan Lv, Yuezun Li, Junyu Dong, Sheng Chen, Hui Yu, Huiyu Zhou, Shu Zhang

Specifically, our strategy considers both forward and backward adaptation, to transfer the forgery knowledge from the source domain to the target domain in forward adaptation and then reverse the adaptation from the target domain to the source domain in backward adaptation.

DeepFake Detection Face Swapping +2

ForensicsForest Family: A Series of Multi-scale Hierarchical Cascade Forests for Detecting GAN-generated Faces

no code implementations2 Aug 2023 Jiucui Lu, Yuezun Li, Jiaran Zhou, Bin Li, Junyu Dong, Siwei Lyu

The proposed ForensicsForest family is composed of three variants, which are {\em ForensicsForest}, {\em Hybrid ForensicsForest} and {\em Divide-and-Conquer ForensicsForest} respectively.

FakeTracer: Proactively Defending Against Face-swap DeepFakes via Implanting Traces in Training

no code implementations27 Jul 2023 Pu Sun, Honggang Qi, Yuezun Li, Siwei Lyu

Face-swap DeepFake is an emerging AI-based face forgery technique that can replace the original face in a video with a generated face of the target identity while retaining consistent facial attributes such as expression and orientation.

Face Generation Face Swapping

Enhancing the Transferability via Feature-Momentum Adversarial Attack

1 code implementation22 Apr 2022 Xianglong, Yuezun Li, Haipeng Qu, Junyu Dong

However, the guidance map is fixed in existing methods, which can not consistently reflect the behavior of networks as the image is changed during iteration.

Adversarial Attack

Imperceptible Adversarial Examples for Fake Image Detection

no code implementations3 Jun 2021 Quanyu Liao, Yuezun Li, Xin Wang, Bin Kong, Bin Zhu, Siwei Lyu, Youbing Yin, Qi Song, Xi Wu

Fooling people with highly realistic fake images generated with Deepfake or GANs brings a great social disturbance to our society.

Face Swapping Fake Image Detection

DeepFake-o-meter: An Open Platform for DeepFake Detection

no code implementations2 Mar 2021 Yuezun Li, Cong Zhang, Pu Sun, Honggang Qi, Siwei Lyu

In recent years, the advent of deep learning-based techniques and the significant reduction in the cost of computation resulted in the feasibility of creating realistic videos of human faces, commonly known as DeepFakes.

DeepFake Detection Face Swapping

Landmark Breaker: Obstructing DeepFake By Disturbing Landmark Extraction

no code implementations1 Feb 2021 Pu Sun, Yuezun Li, Honggang Qi, Siwei Lyu

In this paper, we describe Landmark Breaker, the first dedicated method to disrupt facial landmark extraction, and apply it to the obstruction of the generation of DeepFake videos. Our motivation is that disrupting the facial landmark extraction can affect the alignment of input face so as to degrade the DeepFake quality.

Face Swapping

LandmarkGAN: Synthesizing Faces from Landmarks

no code implementations31 Oct 2020 Pu Sun, Yuezun Li, Honggang Qi, Siwei Lyu

Face synthesis is an important problem in computer vision with many applications.

Face Generation

Exposing GAN-generated Faces Using Inconsistent Corneal Specular Highlights

1 code implementation24 Sep 2020 Shu Hu, Yuezun Li, Siwei Lyu

We show that such artifacts exist widely in high-quality GAN synthesized faces and further describe an automatic method to extract and compare corneal specular highlights from two eyes.

Fast Portrait Segmentation with Highly Light-weight Network

no code implementations19 Oct 2019 Yuezun Li, Ao Luo, Siwei Lyu

In this paper, we describe a fast and light-weight portrait segmentation method based on a new highly light-weight backbone (HLB) architecture.

Portrait Segmentation Segmentation

Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics

7 code implementations CVPR 2020 Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, Siwei Lyu

AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information.

DeepFake Detection Face Swapping

Exposing GAN-synthesized Faces Using Landmark Locations

no code implementations30 Mar 2019 Xin Yang, Yuezun Li, Honggang Qi, Siwei Lyu

Generative adversary networks (GANs) have recently led to highly realistic image synthesis results.

General Classification Image Generation

De-identification without losing faces

no code implementations12 Feb 2019 Yuezun Li, Siwei Lyu

In this work, we describe a new face de-identification method that can preserve essential facial attributes in the faces while concealing the identities.

Attribute De-identification

Exposing Deep Fakes Using Inconsistent Head Poses

1 code implementation1 Nov 2018 Xin Yang, Yuezun Li, Siwei Lyu

In this paper, we propose a new method to expose AI-generated fake face images or videos (commonly known as the Deep Fakes).

General Classification

Exposing DeepFake Videos By Detecting Face Warping Artifacts

3 code implementations1 Nov 2018 Yuezun Li, Siwei Lyu

Compared to previous methods which use a large amount of real and DeepFake generated images to train CNN classifier, our method does not need DeepFake generated images as negative training examples since we target the artifacts in affine face warping as the distinctive feature to distinguish real and fake images.

Face Swapping

Exploring the Vulnerability of Single Shot Module in Object Detectors via Imperceptible Background Patches

no code implementations16 Sep 2018 Yuezun Li, Xiao Bian, Ming-Ching Chang, Siwei Lyu

In this paper, we focus on exploring the vulnerability of the Single Shot Module (SSM) commonly used in recent object detectors, by adding small perturbations to patches in the background outside the object.

Object Region Proposal

Robust Adversarial Perturbation on Deep Proposal-based Models

no code implementations16 Sep 2018 Yuezun Li, Daniel Tian, Ming-Ching Chang, Xiao Bian, Siwei Lyu

Adversarial noises are useful tools to probe the weakness of deep learning based computer vision algorithms.

Instance Segmentation Region Proposal +2

In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye Blinking

3 code implementations7 Jun 2018 Yuezun Li, Ming-Ching Chang, Siwei Lyu

The new developments in deep generative networks have significantly improve the quality and efficiency in generating realistically-looking fake face videos.

Face Swapping

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