Fake videos detection by tracing the source using video hashing retrieval.

Related tags

Deep Learningdeep-learningpytorchhashing-algorithmfake-video-detection
Overview

Vision Transformer Based Video Hashing Retrieval for Tracing the Source of Fake Videos 🎉️

📜 Directory

✨ Introduction

VTL

Video Tracing and Tampering Localization (VTL). A novel framework to detect fake video (clipping, cropping, blur, etc.) by tracing the source video of fake video. 1) Training hash centers as HCs. 2) Finding index of source video from HCs. 3) Masking the different between fake video and source video as a result of comparison (auxiliary information).

Trace Samples and Acc of HashBits

Although the source videos are very similar, we can accurately find the source videos of the fake video clips.

DFTL Dataset Samples

Same person with different scenes. You can download full 16 minutes videos of source video and fake video by follows link.

Different fake videos from same source.

Source Video

Fake Videos of Different Face Swap Methods

DAVIS2016-TL Dataset Samples

The first gif of boat is source video, and remaining five videos generated by different inpainting methods.

🔬 Train or Test

Datasets Download

BaiduNetdisk code：VTLs

  • actors: Source videos and fake videos of full 16 minutes. You can use these videos to make richer datasets.
  • DFTL: Dataset of DFTL, the DFTL build from actors.
  • DAVIS2016-TL: Extension of DAVIS2016

Extract to the same directory as the code (vtl). Example:

├─other files
├─project
│  ├─vrf: dataset of DFTL
│  ├─inpainting: dataset of DAVIS2016-TL
│  └─vtl: our code
│      ├─CSQ: Central Similarity Quantization for Efficient Image and Video Retrieval
│      ├─dmac: Compared method of Localization
│      └─codes

Train

Pretrained models and hash centers

pip install -r requirements.txt

Model DFTL DAVIS2016-TL
ViTHash 64-1024bits 64-1024bits
Generator link link

Parameters

  • local_rank: gpu id
  • path: dataset path
  • type: choice dataloader
    • 0: DFTL dataloader, dir name is vrf
    • 1: DAVIS2016-TL dataloader, dir name is inpainting

Train ViTHash

python train_h.py --local_rank=0 --path=../vrf --type=0 --bits=128

Train Generator

python train_g.py --local_rank=0 --path=../vrf --type=0

Test

Test IOU

The test script will test Generator of VTL and DMAC together on DFTL and DAVIS2016-TL. You can modify it for yourself.

python test_iou.py

Test ViTHash

  1. type: choice dataloader
    • 0: DFTL dataloader, dir name is vrf
    • 1: DAVIS2016-TL dataloader, dir name is inpainting
  2. path: dataset path
  3. hashbits: 128 256 512 or 1024, will load different pre-trained model and hash JSON file.
python test.py 1 ../inpainting 512

Test CSQ

  1. cd ./CSQ
  2. run test script
python hash_test_vrf.py --dataset=Inpainting --pretrained_3d=./Inpainting_64bits.pth

🚀️ Tracing

Trace Samples

👀️ Localization

Localization Samples

DAVIS2016-TL

DFTL

You might also like...
Implementation of accepted AAAI 2021 paper: Deep Unsupervised Image Hashing by Maximizing Bit Entropy
Implementation of accepted AAAI 2021 paper: Deep Unsupervised Image Hashing by Maximizing Bit Entropy

Deep Unsupervised Image Hashing by Maximizing Bit Entropy This is the PyTorch implementation of accepted AAAI 2021 paper: Deep Unsupervised Image Hash

null 62 Dec 30, 2022
Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"

Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"

Ng Kam Woh 71 Dec 22, 2022
Tracing Versus Freehand for Evaluating Computer-Generated Drawings (SIGGRAPH 2021)
Tracing Versus Freehand for Evaluating Computer-Generated Drawings (SIGGRAPH 2021)

Tracing Versus Freehand for Evaluating Computer-Generated Drawings (SIGGRAPH 2021) Zeyu Wang, Sherry Qiu, Nicole Feng, Holly Rushmeier, Leonard McMill

Zach Zeyu Wang 23 Dec 9, 2022
Enhancing Knowledge Tracing via Adversarial Training

Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T

Xiaopeng Guo 14 Oct 24, 2022
Implementation of light baking system for ray tracing based on Activision's UberBake

Vulkan Light Bakary MSU Graphics Group Student's Diploma Project Treefonov Andrey [GitHub] [LinkedIn] Project Goal The goal of the project is to imple

Andrey Treefonov 7 Dec 27, 2022
Ray tracing of a Schwarzschild black hole written entirely in TensorFlow.

TensorGeodesic Ray tracing of a Schwarzschild black hole written entirely in TensorFlow. Dependencies: Python 3 TensorFlow 2.x numpy matplotlib About

null 5 Jan 15, 2022
Space-event-trace - Tracing service for spaceteam events
Space-event-trace - Tracing service for spaceteam events

space-event-trace Tracing service for TU Wien Spaceteam events. This service is

TU Wien Space Team 2 Jan 4, 2022
Activity image-based video retrieval

Cross-modal-retrieval Our approach is focus on Activity Image-to-Video Retrieval (AIVR) task. The compared methods are state-of-the-art single modalit

BCMI 75 Oct 21, 2021
A Joint Video and Image Encoder for End-to-End Retrieval
A Joint Video and Image Encoder for End-to-End Retrieval

Frozen️ in Time ❄️ ️️️️ ⏳ A Joint Video and Image Encoder for End-to-End Retrieval project page | arXiv | webvid-data Repository containing the code,

null 225 Dec 25, 2022
Comments
  • the pre-trained model

    the pre-trained model

    I downloaded the provided pre-trained model and the test acc in DFTL and DAVIS2016-TL reached 100%, is this correct? Why is it so much higher than in the article?

    opened by ymhzyj 1
Releases(v1.0)
Owner
GitHub Repository
TCPNet - Temporal-attentive-Covariance-Pooling-Networks-for-Video-Recognition

Temporal-attentive-Covariance-Pooling-Networks-for-Video-Recognition This is an implementation of TCPNet. Introduction For video recognition task, a g

Zilin Gao 21 Dec 08, 2022
Make your first PR. A beginner friendly repository made specifically for open source beginners. Add any program under any language (it can be anything from a simple program to a complex data structure algorithm). Happy coding...

Hacktober Fest 2021 Upload Different Types of Programs in any Language Use this project to make your first contribution to an open source project on G

Namish Khanna 40 Oct 11, 2022
Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms

LESA Introduction This repository contains the official implementation of Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Cont

Chenglin Yang 20 Dec 31, 2021
A very simple baseline to estimate 2D & 3D SMPL-compatible keypoints from a single color image.

Minimal Body A very simple baseline to estimate 2D & 3D SMPL-compatible keypoints from a single color image. The model file is only 51.2 MB and runs a

Yuxiao Zhou 49 Dec 05, 2022
(NeurIPS '21 Spotlight) IQ-Learn: Inverse Q-Learning for Imitation

Inverse Q-Learning (IQ-Learn) Official code base for IQ-Learn: Inverse soft-Q Learning for Imitation, NeurIPS '21 Spotlight IQ-Learn is an easy-to-use

Divyansh Garg 102 Dec 20, 2022
Automatic Image Background Subtraction

Automatic Image Background Subtraction This repo contains set of scripts for automatic one-shot image background subtraction task using the following

Oleg Sémery 6 Dec 05, 2022
Predicting Tweet Sentiment Maching Learning and streamlit

Predicting-Tweet-Sentiment-Maching-Learning-and-streamlit (I prefere using Visual Studio Code ) Open the folder in VS Code Run the first cell in requi

1 Nov 20, 2021
This repo will contain code to reproduce and build upon understanding transfer learning

What is being transferred in transfer learning? This repo contains the code for the following paper: Behnam Neyshabur*, Hanie Sedghi*, Chiyuan Zhang*.

4 Jun 16, 2021
Code for Contrastive-Geometry Networks for Generalized 3D Pose Transfer

CGTransformer Code for our AAAI 2022 paper "Contrastive-Geometry Transformer network for Generalized 3D Pose Transfer" Contrastive-Geometry Transforme

18 Jun 28, 2022
Cortex-compatible model server for Python and TensorFlow

Nucleus model server Nucleus is a model server for TensorFlow and generic Python models. It is compatible with Cortex clusters, Kubernetes clusters, a

Cortex Labs 14 Nov 27, 2022
The Multi-Mission Maximum Likelihood framework (3ML)

PyPi Conda The Multi-Mission Maximum Likelihood framework (3ML) A framework for multi-wavelength/multi-messenger analysis for astronomy/astrophysics.

The Multi-Mission Maximum Likelihood (3ML) 62 Dec 30, 2022
[LREC] MMChat: Multi-Modal Chat Dataset on Social Media

MMChat This repo contains the code and data for the LREC2022 paper MMChat: Multi-Modal Chat Dataset on Social Media. Dataset MMChat is a large-scale d

Silver 47 Jan 03, 2023
A general python framework for single object tracking in LiDAR point clouds, based on PyTorch Lightning.

Open3DSOT A general python framework for single object tracking in LiDAR point clouds, based on PyTorch Lightning. The official code release of BAT an

Kangel Zenn 172 Dec 23, 2022
Amazing-Python-Scripts - 🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.

📑 Introduction A curated collection of Amazing Python scripts from Basics to Advance with automation task scripts. This is your Personal space to fin

Avinash Ranjan 1.1k Dec 29, 2022
A flag generation AI created using DeepAIs API

Vex AI or Vexiology AI is an Artifical Intelligence created to generate custom made flag design texts. It uses DeepAIs API. Please be aware that you must include your own DeepAI API key. See instruct

Bernie 10 Apr 06, 2022
Distributional Sliced-Wasserstein distance code

Distributional Sliced Wasserstein distance This is a pytorch implementation of the paper "Distributional Sliced-Wasserstein and Applications to Genera

VinAI Research 39 Jan 01, 2023
The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding.

SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you

Yu Meng 38 Dec 12, 2022
Employs neural networks to classify images into four categories: ship, automobile, dog or frog

Neural Net Image Classifier Employs neural networks to classify images into four categories: ship, automobile, dog or frog Viterbi_1.py uses a classic

Riley Baker 1 Jan 18, 2022
Deep Federated Learning for Autonomous Driving

FADNet: Deep Federated Learning for Autonomous Driving Abstract Autonomous driving is an active research topic in both academia and industry. However,

AIOZ AI 12 Dec 01, 2022
Share a benchmark that can easily apply reinforcement learning in Job-shop-scheduling

Gymjsp Gymjsp is an open source Python library, which uses the OpenAI Gym interface for easily instantiating and interacting with RL environments, and

134 Dec 08, 2022