DFSpot-Deepfake-Recognition
autogluon
DFSpot-Deepfake-Recognition | autogluon | |
---|---|---|
9 | 8 | |
89 | 7,124 | |
- | 1.6% | |
0.0 | 9.6 | |
over 1 year ago | 9 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DFSpot-Deepfake-Recognition
-
Detection of DeepFakes
The code for the paper can be found at: https://github.com/chinmaynehate/DFSpot-Deepfake-Recognition
- DeepFake Detection
-
Exposing DeepFakes Using Siamese Training
Code for the paper: https://github.com/chinmaynehate/DFSpot-Deepfake-Recognition
Demo link is available in the Readme of the repository
Results have been obtained on datasets: DFDC, FF++ & CelebDF (V2)
- Detecting DeepFake Videos
- Detect fake videos using deep learning
- DFSpot-Deepfake-Recognition: Determine whether a given video sequence has been manipulated or synthetically generated.
- DeepFake detection using Ensemble Learning
- DFSpot-Deepfake-Recognition: Determine whether a given video sequence has been manipulated or synthetically generated
- DeepFake detection using ensemble and siamese learning
autogluon
-
pip install remyxai - easiest way to create custom vision models
This seems not very convincing. There are other popular frameworks that provide AutoML with existing datasets (eg https://github.com/autogluon/autogluon)
- autogluon: NEW Data - star count:5070.0
-
[D] Where is AutoML for NNs?
https://github.com/awslabs/autogluon works well for image/text/tabular data
- k-fold bagging in Autogluon - Tabular
-
What will the data science job market be like in 5 years?
Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.
What are some alternatives?
deepfake-scanner - Deepfake Scanner by Deepware.
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
AdaTime - [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data
autokeras - AutoML library for deep learning
autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data [Moved to: https://github.com/autogluon/autogluon]
auto-sklearn - Automated Machine Learning with scikit-learn
DeepFake-Detection - Towards deepfake detection that actually works
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
dino-vit-features - Official implementation for the paper "Deep ViT Features as Dense Visual Descriptors".
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
pyc2pa - Python implementation of C2PA: Coalition for Content Provenance and Authenticity.
tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf