kingback2019's Stars
xieyuankun/Codecfake
This is the official repo of our work titled "The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audio".
sroutray/da-ganin
Implementation of Ganin's Paper
cfeng16/audio-visual-forensics
kan-bayashi/ParallelWaveGAN
Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch
imagecbj/Initiative-Defense-against-Voice-Conversion-through-Generative-Adversarial-Network
Implementation code of the paper Initiative Defense against Voice Conversion through Generative Adversarial Network
piotrkawa/specrnet
Implementation of "SpecRNet: Towards Faster and More Accessible Audio DeepFake Detection" paper
SVDDChallenge/CtrSVDD2024_Baseline
Baseline system for SVDD 2024 Challenge CtrSVDD track
gylin2/ocnet
laekov/fastmoe
A fast MoE impl for PyTorch
yongyizang/SingFake
Official Repository for "SingFake: Singing Voice Deepfake Detection"
SVDDChallenge/CtrSVDD_Utils
WUSTL-CSPL/AntiFake
https://dl.acm.org/doi/10.1145/3576915.3623209
georgian-io/Knowledge-Distillation-Toolkit
:no_entry: [DEPRECATED] A knowledge distillation toolkit based on PyTorch and PyTorch Lightning.
yxlu-0102/MP-SENet
MP-SENet: A Speech Enhancement Model with Parallel Denoising of Magnitude and Phase Spectra
khhungg/BSSE-SE
Boosting Self-Supervised Embeddings for Speech Enhancement
winddori2002/MANNER
MANNER: Multi-view Attention Network for Noise ERasure (Speech enhancement in time-domain)
sczhou/CodeFormer
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
weihaox/awesome-digital-human
A collection of resources on digital human including clothed people digitalization, virtual try-on, and other related directions.
zyj-2000/AIGC-Digital-Human
Collections of papers, databases, and codes targeted at Digital Human
Jack-Cherish/AI-Digital-Human
svc-develop-team/so-vits-svc
SoftVC VITS Singing Voice Conversion
Trusted-AI/adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
IBM/Autozoom-Attack
Codes for reproducing query-efficient black-box attacks in “AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks” , published at AAAI 2019
sarathknv/adversarial-examples-pytorch
Implementation of Papers on Adversarial Examples
as791/ZOO_Attack_PyTorch
This repository contains the PyTorch implementation of Zeroth Order Optimization Based Adversarial Black Box Attack (https://arxiv.org/abs/1708.03999)
JHL-HUST/SI-NI-FGSM
hanwei0912/SmoothAdversarialExamples
Smooth Adversarial Examples
ljuvela/CollaborativeWatermarking
mediazypedu/Partial-Spoof-Speech-Detection
talkingnow/HM-Conformer