Face Swapping
192 papers with code • 2 benchmarks • 9 datasets
Face swapping refers to the task of swapping faces between images or in an video, while maintaining the rest of the body and environment context.
( Image credit: Swapped Face Detection using Deep Learning and Subjective Assessment )
Libraries
Use these libraries to find Face Swapping models and implementationsDatasets
Latest papers with no code
DUPE: Detection Undermining via Prompt Engineering for Deepfake Text
Yet the accuracy of many of these detectors has not been thoroughly verified, posing potential harm to students who are falsely accused of academic dishonesty.
Towards More General Video-based Deepfake Detection through Facial Feature Guided Adaptation for Foundation Model
With the rise of deep learning, generative models have enabled the creation of highly realistic synthetic images, presenting challenges due to their potential misuse.
Cross-Domain Audio Deepfake Detection: Dataset and Analysis
Audio deepfake detection (ADD) is essential for preventing the misuse of synthetic voices that may infringe on personal rights and privacy.
D$^3$: Scaling Up Deepfake Detection by Learning from Discrepancy
The boom of Generative AI brings opportunities entangled with risks and concerns.
Real, fake and synthetic faces - does the coin have three sides?
This observation was supported by further analysis of various image properties.
Diffusion Deepfake
To address this critical issue, we investigate the impact of enhancing training data diversity on representative detection methods.
Generation and Detection of Sign Language Deepfakes - A Linguistic and Visual Analysis
A question in the realm of deepfakes is slowly emerging pertaining to whether we can go beyond facial deepfakes and whether it would be beneficial to society.
FlashFace: Human Image Personalization with High-fidelity Identity Preservation
This work presents FlashFace, a practical tool with which users can easily personalize their own photos on the fly by providing one or a few reference face images and a text prompt.
Exploring Green AI for Audio Deepfake Detection
In contrast to existing methods that fine-tune SSL models and employ additional deep neural networks for downstream tasks, we exploit classical machine learning algorithms such as logistic regression and shallow neural networks using the SSL embeddings extracted using the pre-trained model.
Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection
We propose to train detectors using only pristine images injecting in part of them crafted frequency patterns, simulating the effects of various deepfake generation techniques without being specific to any.