Generate synthetic image using DCGAN on fashion mnist data
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Updated
Aug 27, 2021 - Python
Generate synthetic image using DCGAN on fashion mnist data
Helpful resources for creating deepfakes.
Towards deepfake detection that actually works
DeepFakeLab is a powerful repository for image manipulation using cutting-edge generative models. Easily insert various features into images, explore creative possibilities, and learn about advanced generative techniques. This repository is both a practical tool and an educational resource for computer vision enthusiasts.
Some code from our attempt to tackle Deep Fakes
Implementation of the winning solution for the Media Analytics Challenge 2023.
A poor attempt to implement a DeepFake/FaceSwap using Pytorch and OpenCV
Provides a framework for training Generative Adverserial Networks (GANs) with user-defined training parameters and network complexity.
This is a paper on deepfake generation and how to evaluate it.
[ICPR 2024] The official repo for FIDAVL: Fake Image Detection and Attribution using Vision-Language Model
one-click face swap
Deep fake detection using cnn, Xception, Denesenet121, GAN on four different datasets.
Thesis topic of M.Tech final year from IIIT Allahabad
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