California

Le Minh Binh

Expert
@Leminhbinh0209

Ph.D. student in Computer Science @ SKKU, South Korea

CVPR24-FAS. Official implementation of CVPR24 paper "Gradient Alignment for Cross-Domain Face Anti-Spoofing"

84

F3Net. Unofficial implementation of ECCV20 paper "Thinking in frequency: Face forgery detection by mining frequency-aware clues"

67

FinetuneVAE-SD. Fine-tune VAE of Stable Diffusion model

59

AAAI22-ADD. Official implementation of AAAI22 paper "ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images"

10

Springer-books. Free Springer book of Maths and Computer science

7

AsyncGAN. Official implementation of Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images (IJCAI Workshop 2021)

7

GANFingerprints-pytorch. Unofficial PyTorch implementation of Paper titled "Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints" ( ICCV 2019)

5

LookSAM. Unofficial Implementation of "Towards Efficient and Scalable Sharpness-Aware Minimization"

3

CLIP-Surgery-Simple. This respository help you to add self-self attention without create new model

3

Samba. Official implementation of CIKM22 paper "Samba: Identifying Inappropriate Videos for Young Children on YouTube"

3

KappaFace. Official Implementation of IEEE Access paper "KappaFace: Adaptive Additive Angular Margin Loss for Deep Face Recognition"

3

ICCV23-QAD. Official implementation of ICCV23 paper "QAD: Quality-Agnostic Deepfake Detection with Intra-model Collaborative Learning"

2

Pareidolia. Official implementation of AAAI26 paper "Machine Pareidolia: Protecting Facial Image with Emotional Editing"

2

SoTA-Deepfakes-Detector-Statistics. This repository provide the most SoTA deepfake detectors' performances on 11 deepfakedatasets

1

deepfake-cls. A simple deepfake type classifier

1

Empir. Official implementation of Expectation-Maximization via Pretext-Invariant Representations. (IEEE Access 2023)

1

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

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