The approach I work on DeepFake.
The approach I work on DeepFake.
And I find a very interesting website which could generate human face via Deepfake tech and it makes its code open source which could help us learn.
| Datasets | Year | Ratio tampered:original |
Total videos | Source | Participants Consent | Tools |
|---|---|---|---|---|---|---|
| UADFV | 2018 | 1 : 1.00 | 98 | YouTube | N | FakeAPP |
| FaceForensics | 2018 | 1 : 1.00 | 2008 | YouTube | N | Face2Face |
| Deepfake-TIMIT | 2019 | 1 : 1.00 | 620 | Vid-TIMIT | N | faceswap-GAN |
| FaceForensics++ | 2019 | 1 : 0.25 | 5000 | YouTube | N | faceswap DeepFake Face2Face NeuralTextures |
| DeepFakeDetection (part of FaceForensics++) |
2019 | 1 : 0.12 | 3363 | Actors | Y | |
| Celeb-DF | 2019 | 1 : 0.51 | 1203 | YouTube | N | a refined version of the DeepFake |
| DFDC Preview Dataset | 2019 | 1 : 0.28 | 5214 | Actors | Y | Unkonwn |
| Name | Description | Demo | Popularity |
|---|---|---|---|
| Grover | Grover is a model for Neural Fake News — both generation and detection. However, it probably can also be used for other generation tasks. | https://grover.allenai.org/ |
gpt-2xy | GPT-2 User Interface based on HuggingFace’s Pytorch Implementation | https://gpt2.ai-demo.xyz/ | |
CTRL | Conditional Transformer Language Model for Controllable Generation | N/A | |
Talk to Transformer | See how a modern neural network completes your text. Type a custom snippet or try one of the examples | https://talktotransformer.com | N/A |
LEO | First intelligent system for creating news in Spanish | N/A | N/A
Big Bird | Bird Bird uses State of the Art (SOTA) Natural Language Processing to aid your fact-checked and substantive content. | BigBirdDemo| N/A
aitextgen | A robust Python tool for text-based AI training and generation using GPT-2.| Demo |
GPT-3 | GPT-3: Language Models are Few-Shot Learners | N/A |
| Name | Description | Demo | Popularity |
|---|---|---|---|
Real-Time-Voice-Cloning | Clone a voice in 5 seconds to generate arbitrary speech in real-time | https://www.youtube.com/watch?v=-O_hYhToKoA |
Lyrebird | Create your own vocal avatar! | N/A | N/A |
Descrypt | Record. Transcribe. Edit. Mix. As easy as typing. | N/A | N/A
Common Voice | Common Voice is Mozilla’s initiative to help teach machines how real people speak. | N/A | N/A
Resemble.ai | Resemble can clone any voice so it sounds like a real human. | N/A | N/A
TacoTron | Tacotron (/täkōˌträn/): An end-to-end speech synthesis system by Google. | Demo |
Sonantic | Create a captivating performance using emotionally expressive text-to-speech. | Demo | N/A
15.ai | Natural text-to-speech synthesis with minimal data. | Demo | N/A
| Name | Description | Demo | Popularity |
|---|---|---|---|
StyleGAN | An alternative generator architecture for generative adversarial networks, borrowing from style transfer literature. The new architecture leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose and identity when trained on human faces) and stochastic variation in the generated images (e.g., freckles, hair), and it enables intuitive, scale-specific control of the synthesis. The new generator improves the state-of-the-art in terms of traditional distribution quality metrics, leads to demonstrably better interpolation properties, and also better disentangles the latent factors of variation. | https://www.youtube.com/watch?v=kSLJriaOumA |
StyleGAN2 | Improved version for StyleGAN. | https://www.youtube.com/watch?v=c-NJtV9Jvp0 |
| DG-Net | Joint Discriminative and Generative Learning for Person Re-identification | https://www.youtube.com/watch?v=ubCrEAIpQs4 |
| GANSpace | Discovering Interpretable GAN Controls | http://www.exploreganspace.com/ |
|StarGAN v2 | StarGAN v2 - Official PyTorch Implementation (CVPR 2020) | https://youtu.be/0EVh5Ki4dIY |
Image GPT | Image GPT | N/A |
FQ-GAN | Official implementation of FQ-GAN | http://40.71.23.172:8888 |
|EHM_Faces | EHM_Faces is a machine learning project that can generate high-quality, realistic ice hockey player portraits. Primarily meant for the game Eastside Hockey Manager (EHM), this project can generate portraits either one-at-a-time or in batches (the resulting batches are called facepacks). | N/A |
|Rewriting a Deep Generative Model | Edits the weights of a deep generative network by rewriting associative memory directly, without training data | Demo |
|Semantic Image Synthesis with SPADE | Semantic Image Synthesis with Spatially-Adaptive Normalization in CVPR. | Demo Page |
| Name | Description | Demo | Popularity |
|---|---|---|---|
| FaceSwap | Grover is a model for Neural Fake News — both generation and detection. However, it probably can also be used for other generation tasks. | https://www.youtube.com/watch?v=r1jng79a5xc |
Face2Face | FaceSwap is a tool that utilizes deep learning to recognize and swap faces in pictures and videos. | N/A | |
Faceswap | FaceSwap is an app that I have originally created as an exercise for my students in “Mathematics in Multimedia” on the Warsaw University of Technology. | N/A | |
Faceswap-GAN | Adding Adversarial loss and perceptual loss (VGGface) to deepfakes’(reddit user) auto-encoder architecture. | https://github.com/shaoanlu/faceswap-GAN/blob/master/colab_demo/faceswap-GAN_colab_demo.ipynb | |
DeepFaceLab | DeepFaceLab is a tool that utilizes machine learning to replace faces in videos. | https://www.youtube.com/watch?v=um7q--QEkg4 | |
Vid2Vid | Pytorch implementation for high-resolution (e.g., 2048x1024) photorealistic video-to-video translation. | https://www.youtube.com/watch?v=5zlcXTCpQqM | |
DFaker | Pytorch implementation for high-resolution (e.g., 2048x1024) photorealistic video-to-video translation. | N/A | |
Image Animation | The videos on the left show the driving videos. The first row on the right for each dataset shows the source videos. | https://www.youtube.com/watch?v=mUfJOQKdtAk | |
Avatarify | Photorealistic avatars for Skype and Zoom. Democratized. Based on First Order Motion Model.. | https://www.youtube.com/watch?v=lONuXGNqLO0 | |
Speech driven animation | This library implements the end-to-end facial synthesis model. | N/A | |
| Name | Description | Demo | Popularity |
|---|---|---|---|
| Grover | Grover is a model for Neural Fake News — both generation and detection. However, it probably can also be used for other generation tasks. | https://grover.allenai.org/ |
GLTR | Detecting text that was generated from large language models (e.g. GPT-2). | http://gltr.io/dist/index.html | |
fake news detection | In this project, we aim to build state-of-the-art deep learning models to detect fake news based on the content of article itself. | Demo | |
GPTrue or False | Display the likelihood that a sample of text was generated by OpenAI’s GPT-2 model. | N/A | N/A |
| Name | Description | Demo | Popularity |
|---|---|---|---|
| Spooded speech detection | This work is part of the “DDoS Resilient Emergency Dispatch Center” project at the University of Houston, funded by the Department of Homeland Security (DHS). | N/A |
Fake voice detection | This repository provides the code for a fake audio detection model built using Foundations Atlas. It also includes a pre-trained model and inference code, which you can test on any of your own audio files. | N/A |
Fake Voice Detector | For “Deep Learning class” at ETHZ. Evaluate how well the fake voice of Barack Obama 1. confuses the voice verification system, 2. can be detected. | N/A |
CycleGAN Voice Converter | An implementation of CycleGAN on human speech conversions | https://leimao.github.io/project/Voice-Converter-CycleGAN/ |
| Name | Description | Demo | Popularity |
|---|---|---|---|
| FALdetector | Detecting Photoshopped Faces by Scripting Photoshop. | https://www.youtube.com/watch?v=TUootD36Xm0 |
| Name | Description | Demo | Popularity |
|---|---|---|---|
| FaceForensics++ | FaceForensics++ is a forensics dataset consisting of 1000 original video sequences that have been manipulated with four automated face manipulation methods: Deepfakes, Face2Face, FaceSwap and NeuralTextures. | https://www.youtube.com/watch?v=x2g48Q2I2ZQ | |
| Face Artifacts | Our method is based on the observations that current DeepFake algorithm can only generate images of limited resolutions, which need to be further warped to match the original faces in the source video. | N/A |
DeepFake-Detection | Our Pytorch implementation, conducts extensive experiments to demonstrate that the datasets produced by Google and detailed in the FaceForensics++ paper are not sufficient for making neural networks generalize to detect real-life face manipulation techniques. | http://deepfake-detection.dessa.com/projects | |
Capsule-Forensics-v2 | Implementation of the paper: Use of a Capsule Network to Detect Fake Images and Videos. | N/A | |
ClassNSeg | Implementation of the paper: Multi-task Learning for Detecting and Segmenting Manipulated Facial Images and Videos (BTAS 2019). | N/A | |
| fakeVideoForensics | Fake video detector | https://www.youtube.com/watch?v=8YYRT4lzQgY |
