Deepfake Generation

Deepfake generation involves creating realistic synthetic media, primarily images and videos, often using individuals' likenesses without their consent. Current research focuses on improving the realism of deepfakes through advanced generative models like diffusion models and GANs, as well as developing robust detection methods that leverage techniques such as analyzing frequency patterns, identifying inconsistencies across modalities (e.g., audio-visual discrepancies), and employing ensemble methods combining 2D and 3D convolutional neural networks or vision transformers. The ability to generate highly realistic deepfakes poses significant challenges for identifying misinformation and protecting individual privacy, driving intense research efforts to develop both more sophisticated generation and detection techniques.